{"id":5501,"date":"2015-11-09T18:24:22","date_gmt":"2015-11-10T00:24:22","guid":{"rendered":"http:\/\/gisgeography.com\/?p=5501"},"modified":"2025-04-09T05:11:23","modified_gmt":"2025-04-09T10:11:23","slug":"gis-dictionary-definition-glossary","status":"publish","type":"post","link":"https:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/","title":{"rendered":"GIS Dictionary &#8211; Geospatial Definition Glossary"},"content":{"rendered":"\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"850\" height=\"360\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature.jpg\" alt=\"GIS Dictionary Glossary Feature\" class=\"wp-image-61349\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature.jpg 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-300x127.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-678x287.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-768x325.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-50x21.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-80x35.jpg 80w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-620x264.jpg 620w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-174x74.jpg 174w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-200x85.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-425x180.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-550x233.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-115x49.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/GIS-Dictionary-Feature-360x152.jpg 360w\" sizes=\"auto, (max-width: 850px) 100vw, 850px\" \/><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">The Ultimate GIS Dictionary: Your Complete Guide to GIS<\/h3>\n\n\n\n<p>GIS is more than just <em>&#8220;maps and data&#8221;<\/em>. Instead, it&#8217;s multi-disciplinary.<\/p>\n\n\n\n<p>It impacts various sectors and uses different skill sets.<\/p>\n\n\n\n<p>That\u2019s why we\u2019ve put together this list of GIS definitions to give you 20\/20 vision.<\/p>\n\n\n\n<p>From A to Z, sharpen your GIS knowledge with these <strong>GIS dictionary<\/strong> definitions and meanings.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Jump to Letter<\/h3>\n\n\n\n<p><a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#A\">A<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#B\">B<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#C\">C<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#D\">D<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#E\">E<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#F\">F<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#G\">G<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#H\">H<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#I\">I<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#J\">J<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#K\">K<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#L\">L<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#M\">M<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#N\">N<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#O\">O<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#P\">P<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#Q\">Q<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#R\">R<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#S\">S<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#T\">T<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#U\">U<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#V\">V<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#W\">W<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#X\">X<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#Y\">Y<\/a> | <a href=\"http:\/\/gisgeography.com\/gis-dictionary-definition-glossary\/#Z\">Z<\/a><\/p>\n\n\n\n<p><a name=\"A\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">A<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"164\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/02\/Passive-Active-Sensors-300x164.jpg\" alt=\"Passive Active Sensors\" class=\"wp-image-96190\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/02\/Passive-Active-Sensors-300x164.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/02\/Passive-Active-Sensors-678x370.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/02\/Passive-Active-Sensors-768x419.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/02\/Passive-Active-Sensors.jpg 850w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Active Sensors<\/strong>: <em>[Remote sensing]<\/em> Active sensors illuminates their target and measure the reflected backscatter that returns back to the sensor.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Adjacency-1-150x100.png\" alt=\"Adjacency\" class=\"wp-image-5042\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Adjacency<\/strong>: <em>[geometry]<\/em> Adjacency occurs when two objects share the same boundary and are next to or adjoining with a common side or vertex.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/AVHRR-NASA-Image-150x100.jpg\" alt=\"AVHRR Sea Surface Temperature\" class=\"wp-image-5043\"\/><\/figure>\n<\/div>\n\n\n<p> <strong>Advanced Very High Resolution Radiometer (AVHRR)<\/strong>: <em>[Remote sensing]<\/em> AVHRR collects infrared, visible, and thermal images with an approximate 1-kilometer spatial resolution cell size.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3-150x100.png\" alt=\"Affine Transformation\" class=\"wp-image-5178\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Affine-Transformation-3.png 225w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p> <strong>Affine transformation<\/strong>: <em>[geometry]<\/em> An affine transformation scales, rotates, skews, or translates points, polylines, and polygons preserving points, straight lines, and planes.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Arc-150x100.png\" alt=\"Arc\" class=\"wp-image-4629\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Arc<\/strong>: <em>[data structure]<\/em> Arcs are lines or polygon boundaries, represented as a series of vertices or coordinate points.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/ArcCatalog-150x100.png\" alt=\"ArcCatalog\" class=\"wp-image-4634\"\/><\/figure>\n<\/div>\n\n\n<p><strong>ArcCatalog<\/strong>: <em>[software]<\/em> ArcCatalog is an application in the ArcGIS suite for managing geographic data \u2013 similar to windows file explorer. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/arcgis-150x100.jpg\" alt=\"Esri ArcGIS\" class=\"wp-image-3901\"\/><\/figure>\n<\/div>\n\n\n<p><strong>ArcGIS<\/strong>: <em>[software]<\/em> ArcGIS is a GIS software package produced by the Environmental Systems Research Institute (Esri) which allows you to collect, store, manage, visualize, export, analyze and map geographic data. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/06\/esri-arcgis-pro-software-0-150x100.png\" alt=\"esri arcgis pro software\" class=\"wp-image-14700\"\/><\/figure>\n<\/div>\n\n\n<p><strong>ArcGIS Pro<\/strong>: <em>[software]<\/em> ArcGIS Pro is Esri&#8217;s latest GIS software with a ribbon-based user interface, project files and 64-bit processing. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/ArcGlobe-150x100.png\" alt=\"ArcGlobe\" class=\"wp-image-4637\"\/><\/figure>\n<\/div>\n\n\n<p><strong>ArcGlobe<\/strong>: <em>[software]<\/em> ArcGlobe is a 3D visualization and analysis environment as part of the Esri ArcGIS suite (3D analyst), specializing in global datasets and larger study areas. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/ArcScene-150x100.png\" alt=\"ArcScene\" class=\"wp-image-4640\"\/><\/figure>\n<\/div>\n\n\n<p><strong>ArcScene<\/strong>: <em>[software]<\/em> ArcScene is a 3D feature and raster viewer part of the Esri ArcGIS suite of applications (3D analyst) specializing in small study area scenes. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii-150x100.png\" alt=\"ascii\" class=\"wp-image-5191\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ascii.png 225w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>American Standard Code for Information Interchange (ASCII)<\/strong>: <em>[file format]<\/em> ASCII uses a set of numbers between 0 and 255 for information storage and processing. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Aspect-150x100.jpg\" alt=\"Aspect Map\" class=\"wp-image-4648\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Aspect-150x100.jpg 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Aspect-50x32.jpg 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Aspect<\/strong>: <em>[GIS processing]<\/em> Aspect is the slope direction on a terrain surface measured clockwise starting north as 0\u00b0 to 360\u00b0 north again with flat areas given a value of -1 or 0 degree. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Atmospheric-Window-1-150x100.png\" alt=\"Atmospheric Window\" class=\"wp-image-5205\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Atmospheric window<\/strong>: <em>[remote sensing]<\/em> An atmospheric window are wavelengths at which electromagnetic radiation (sunlight) from the sun will penetrate the Earth\u2019s atmosphere overall constricting these spectrum bands from reaching the Earth. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/attribute-table-example-gis-dictionary-150x100.png\" alt=\"attribute table\" class=\"wp-image-5199\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/attribute-table-example-gis-dictionary-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/attribute-table-example-gis-dictionary-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/attribute-table-example-gis-dictionary-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/attribute-table-example-gis-dictionary.png 160w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Attribute table<\/strong>: <em>[data structure]<\/em> An attribute table stores non-spatial information in columns and rows about geographic data \u2013 similar to spreadsheets. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/azimuth-150x100.png\" alt=\"azimuth\" class=\"wp-image-5213\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Azimuth<\/strong>: <em>[surveying]<\/em> An azimuth is an angle between 0\u00b0 and 360\u00b0 measured clockwise from north based on true north &#8211; Magnetic azimuths are based on magnetic north. <\/p>\n\n\n\n<p><a name=\"B\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">B<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-base-station-1-150x100.png\" alt=\"survey base station\" class=\"wp-image-5203\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Base station<\/strong>: <em>[surveying]<\/em> A base station is a precisely surveyed location used as a fixed Global Navigation Satellite System (GNSS) recording station, typically used in differential correction. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"217\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Basemap-1-300x217.jpg\" alt=\"Basemap\" class=\"wp-image-96222\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Basemap-1-300x217.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Basemap-1-678x490.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Basemap-1-768x555.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Basemap-1.jpg 800w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Basemap<\/strong>: <em>[cartography]<\/em> A basemap is a background, non-editable, georeferenced image that gives a point of reference on a map, providing aesthetic appeal such as aerial imagery, topography, terrain, and street layers.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bearing-150x100.png\" alt=\"Bearing\" class=\"wp-image-5210\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Bearing<\/strong>: <em>[surveying]<\/em> A bearing is a direction expressed as a geographic angle measured from a baseline used in surveying and navigation. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark-150x100.png\" alt=\"Geodetic survey benchmark\" class=\"wp-image-5216\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodetic-survey-benchmark.png 225w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Benchmark<\/strong>: <em>[surveying]<\/em> Benchmarks are precisely surveyed points usually marked with brass or metal disk in the ground also genetically called survey marks, geodetic marks, and control stations.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-150x100.png\" alt=\"Bilinear interpolation\" class=\"wp-image-5219\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/bilinear-interpolation-1-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Bilinear interpolation<\/strong>: <em>[mathematics]<\/em> Bilinear interpolation is a technique for calculating values of a grid location by taking the weighted average of the four neighboring cells in an image to generate new values.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-150x100.png\" alt=\"Boolean algebra Venn Diagram\" class=\"wp-image-5221\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/boolean-algebra-venn-diagram-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Boolean Algebra<\/strong>: <em>[mathematics]<\/em> Boolean algebra are conditions used to select features with a set of algebraic conditions including AND, OR, or NOT.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-150x100.png\" alt=\"Buffer Line\" class=\"wp-image-5223\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Buffer-Line-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Buffer<\/strong>: <em>[GIS processing]<\/em> The buffer tool is a proximity function that creates a polygon at a set distance surrounding a selected feature or features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-150x100.png\" alt=\"Bundle Adjustment\" class=\"wp-image-5225\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Bundle-Adjustment.png 450w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Bundle adjustment<\/strong>: <em>[geometry]<\/em> Bundle adjustments remove geometric distortions given a set of images of three-dimensional points at different viewpoints, minimizing the error between observed and predicted image points during reprojection. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"C\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">C<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-150x100.png\" alt=\"Carrier phase GPS\" class=\"wp-image-5228\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/carrier-phase-gps.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Carrier-phase GPS<\/strong>: <em>[surveying]<\/em> Carrier-phase GPS signals are relatively slow but are very accurate (within 10cm or better) to determine position on the ground. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-150x100.png\" alt=\"Cartesian Coordinates\" class=\"wp-image-5239\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cartesian-Coordinates-1.png 350w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Cartesian coordinate<\/strong>: <em>[surveying]<\/em> A Cartesian coordinate system specifies each point uniquely with a pair of numerical coordinates or tripless for three-dimensional coordinate spaces. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"200\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Cartography-300x200.jpg\" alt=\"Cartography\" class=\"wp-image-96240\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Cartography-300x200.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Cartography.jpg 600w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Cartography<\/strong>: <em>[GIS dictionary]<\/em> Cartography is the study, aesthetics and science of representing real-world entities on maps by communicating spatial information. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-150x100.png\" alt=\"Cartometry\" class=\"wp-image-5241\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/cartometry-1-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Cartometry<\/strong>: <em>[GIS dictionary]<\/em> Cartometry is a division of cartography concerned with depicting objects with a high level of spatial accuracy such as measuring the perimeter of coasts, areas of countries, volumes, slopes, and densities. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-150x100.png\" alt=\"Centroid\" class=\"wp-image-5243\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Centroid.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Centroid<\/strong>: <em>[geometry]<\/em> A centroid (or geometric center) is a central point of an area feature that represents the average position of all the points in the shape.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Clip-150x100.png\" alt=\"Clip Tool\" class=\"wp-image-4444\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Clip<\/strong>: <em>[geometry]<\/em> A clip is an overlay tool that involves clipping an input layer to the extent of a defined feature boundary.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-150x100.png\" alt=\"Code-Phase GPS\" class=\"wp-image-5247\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Code-Phase-GPS-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Code-Phase GPS<\/strong>: <em>[GPS]<\/em> The coarse acquisition (C\/A) code or code-phase GPS, which is available to the general public, is a GPS signal that delivers rapid, low accuracy position estimates in tens of meters.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-150x100.png\" alt=\"Editing COGO Traverse\" class=\"wp-image-20401\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-COGO-Traverse.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Coordinate Geometry (COGO)<\/strong>: <em>[editing]<\/em> COGO involves the entry of spatial coordinate data points, usually obtained from field survey equipment. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-150x100.png\" alt=\"CAD schematic\" class=\"wp-image-5343\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/CAD-schematic.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Computer Aided Design\/Drafting (CAD)<\/strong>: <em>[GIS dictionary]<\/em> CAD is primarily used by engineers and architects for the purpose of producing two and three-dimensional drawings.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/world-map-150x100.png\" alt=\"World Map Projection\" class=\"wp-image-1167\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Conformal Projection<\/strong>: <em>[map projection]<\/em> A conformal map projection preserves the correct shapes of small areas with the scale being the same in all directions and greatly distorted areas. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equidistant-Conic-Projection-World-150x100.png\" alt=\"Equidistant Conic Projection (World)\" class=\"wp-image-4491\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Conic Projection<\/strong>: <em>[map projection]<\/em> A conic projection uses a cone to develop its surface on a plane with meridians converging at a single point. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Connectivity-1-150x100.png\" alt=\"Connectivity\" class=\"wp-image-5236\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Connectivity-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Connectivity-1-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Connectivity-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Connectivity-1.png 200w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Connectivity<\/strong>: <em>[geometry]<\/em> Connectivity is the representation of the connectedness of linear features when arcs share a common node. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-150x100.png\" alt=\"Continuous Raster\" class=\"wp-image-5249\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Continusous-Raster-1-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Continuous raster<\/strong>: <em>[data structure]<\/em> Continuous rasters are grid cells with gradually changing data such as Digital Elevation Models (DEM), temperature data or distance from features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/contours-150x100.png\" alt=\"Contours\" class=\"wp-image-5263\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Contour Line<\/strong>: <em>[data structure]<\/em> A contour line is a constant value for mapping any variable such as elevation, temperature, isopleth or isoline maps. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"129\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-300x129.jpg\" alt=\"National Geodetic Survey Explorer\" class=\"wp-image-96224\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-300x129.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-678x292.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-768x331.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Control point<\/strong>: <em>[coordinate system]<\/em> Control points are locations known to have a high degree of accuracy that are used to convert digitized coordinates from paper maps and georeferencing to standard map projection coordinates. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-150x100.png\" alt=\"Coordinate Transformation\" class=\"wp-image-5259\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2.png 400w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Coordinate-Transformation-2-232x155.png 232w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Coordinate Transformation<\/strong>: <em>[coordinate system]<\/em> A coordinate transformation is the conversion from a non-projected coordinate system to a coordinate system using a series of mathematical equations. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/latitude-longitude-map-150x100.png\" alt=\"\" class=\"wp-image-4460\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Coordinates<\/strong>: <em>[coordinate system]<\/em> Coordinates are pairs (X, Y) or triplets (X, Y, Z) of values that are used to represent points and features in a two and three-dimensional space. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-150x100.png\" alt=\"Cubic Convolution\" class=\"wp-image-5254\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Cubic-Convolution-11-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Cubic Convolution Interpolation<\/strong>: <em>[mathematics]<\/em> Cubic convolution interpolation averages the 16 nearest cells, which is generally used for continuous surfaces where much noise exists. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Plate-Carree-Projection-150x100.png\" alt=\"Plate Carr\u00e9e Projection\" class=\"wp-image-4523\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Cylindrical Projection<\/strong>: <em>[map projection]<\/em> A cylindrical projection uses a cylinder to develop a plane surface such as Mercator and Plate Carree projections. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"D\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">D<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Raster-Data-Models-150x100.png\" alt=\"Vector Raster Data Models\" class=\"wp-image-5256\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Data Model<\/strong>: <em>[data structure]<\/em> The two main GIS data models are rasters (pixels with a specific cell size) and vectors (points, lines and polygons).<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-150x100.png\" alt=\"Database Management System\" class=\"wp-image-5257\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS.png 400w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DBMS-232x155.png 232w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Database Management System (DBMS)<\/strong>: <em>[data structure]<\/em> A DBMS is a collection of tools that allows the entry, storage, input, output and organization of data, serving as an interface between users and a database. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-150x100.png\" alt=\"Database schema\" class=\"wp-image-5261\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/database-schema.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Database Schema<\/strong>: <em>[data structure]<\/em> A database schema is supported in relational database management systems (RDBMS) and acts as blueprints for how database entries will be constructed. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-150x100.png\" alt=\"Developable Surface\" class=\"wp-image-5268\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Developable-Surface1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Developable Surface<\/strong>: <em>[map projection]<\/em> A developable surface (cylinders, cones, planes, etc) is the geometric shape that a map projection can be mathematically built on. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-150x100.png\" alt=\"Differential GNSS\" class=\"wp-image-5269\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/differential-gnss.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Differential Global Navigation Satellite System (GNSS)<\/strong>: <em>[surveying]<\/em> Differential GNSS is a highly accurate (within centimeters) conventional surveying technique that uses a known location from a receiver to determine an unknown position.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digital-Elevation-Model-DEM-2-150x100.png\" alt=\"Digital Elevation Model (DEM)\" class=\"wp-image-4531\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Elevation Model (DEM)<\/strong>: <em>[GIS processing]<\/em> A Digital Elevation Model (DEM) is a bare earth elevation model representing the surface of the Earth without features like houses, bridges, and trees.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-150x100.png\" alt=\"Digital Line Graph\" class=\"wp-image-5272\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/digital-line-graph-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Line Graph (DLG)<\/strong>: <em>[file format]<\/em> DLG is vector data format developed and distributed by the United States Geological Survey (USGS) depicting geographic features like terrain, hydrography, transportation and man-made features.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-150x100.png\" alt=\"DOQ\" class=\"wp-image-5276\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1.png 400w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DOQ-1-232x155.png 232w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Orthophotos Quadrangle (DOQ)<\/strong>: <em>[file format]<\/em> DOQ is a geometrically-corrected photograph produced by the USGS with a scale of 1:40,000 and spatial resolution of about 1-meter pixels. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-150x100.png\" alt=\"DRG\" class=\"wp-image-5275\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/DRG.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Raster Graphics (DRG)<\/strong>: <em>[file format]<\/em> DRG is a digital version map of USGS topographic maps including imagery (NAIP), roads, place names, hydrography, elevation contours, and boundaries. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"172\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/03\/Digital-Surface-Model-300x172.jpg\" alt=\"Digital Surface Model\" class=\"wp-image-96243\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/03\/Digital-Surface-Model-300x172.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/03\/Digital-Surface-Model-678x388.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/03\/Digital-Surface-Model-768x439.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/03\/Digital-Surface-Model.jpg 850w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Surface Model (DSM)<\/strong>: <em>[file format]<\/em> A digital surface model is an elevation model that includes the top of buildings, tree canopy, powerlines and other features above the bare earth. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digital-Elevation-Model-150x100.jpg\" alt=\"Digital Elevation Model\" class=\"wp-image-4649\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digital-Elevation-Model-150x100.jpg 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digital-Elevation-Model-50x32.jpg 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digital Terrain Model (DTM)<\/strong>: <em>[file format]<\/em> DTM is a bare earth representation of the Earth\u2019s surface that is augmented by natural features such as ridges and breaklines. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-150x100.png\" alt=\"Digitize\" class=\"wp-image-5278\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Digitize.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Digitize<\/strong>: <em>[editing]<\/em> When you digitize in a GIS, you are creating geographic computer-compatible stored data with lines, points, and polygons in a spatial database. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-150x100.png\" alt=\"Dissolve Tool\" class=\"wp-image-5279\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Dissolve-Tool1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Dissolve tool<\/strong>: <em>[GIS processing]<\/em> The dissolve tool is a common GIS processing task where boundaries are merged with neighboring boundaries based on common attribute values. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"E\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">E<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-150x100.png\" alt=\"Easting\" class=\"wp-image-5282\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Easting.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Easting<\/strong>: <em>[coordinate system]<\/em> Eastings refer to the x-axis (eastward) points approximately parallel to lines of equal latitude commonly used in the Universal Transverse Mercator map projection. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-150x100.png\" alt=\"Electromagnetic radiation\" class=\"wp-image-5284\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-768x512.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-550x366.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/electromagnetic-radiation.png 800w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Electromagnetic (EM) Spectrum<\/strong>: <em>[remote sensing]<\/em> The EM spectrum refers to the range of energy wavelengths or frequencies from x-rays, ultraviolet, visible, infrared, and microwave to radio waves. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Ellipsoid1-150x100.png\" alt=\"Ellipsoid\" class=\"wp-image-5289\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Ellipsoid<\/strong>: <em>[surveying]<\/em> Reference ellipsoids are mathematical models of the shape of the Earth with the major axis along the equatorial radius, primarily used as a surface to specify point coordinates such as latitude (north\/south), longitude (east\/west) and elevation (height). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Ellipsoid-height-150x100.png\" alt=\"Ellipsoid Height\" class=\"wp-image-4564\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Ellipsoid Height<\/strong>: <em>[surveying]<\/em> The ellipsoid height is the height measured from an ellipsoidal surface to a point on the surface of the Earth. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Flightline-Endlap-2-150x100.png\" alt=\"Flightline - Endlap\" class=\"wp-image-4569\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Endlap<\/strong>: <em>[remote sensing]<\/em> Endlap is the coverage overlap in aerial photographs from end to end between flight lines. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"200\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/Landsat-7-300x200.jpg\" alt=\"Landsat-7\" class=\"wp-image-96248\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/Landsat-7-300x200.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/Landsat-7.jpg 600w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p> <strong>Enhanced Thematic Mapper (ETM+)<\/strong>: <em>[remote sensing]<\/em> ETM+ is a sensor equipped on Landsat-7 which produces images of Earth in 8 spectral bands (blue, green, red, NIR, MIR, panchromatic, and thermal band). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-150x100.png\" alt=\"Point entity\" class=\"wp-image-5295\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/point-entity.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Entity<\/strong>: <em>[cartography]<\/em> Entities represent a real-world point, line, or polygon features with a geographic location such as fire hydrants, hospitals, state boundaries, roads, rivers, lakes, etc. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-150x100.png\" alt=\"Equal Interval Classification\" class=\"wp-image-5299\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Equal-Interval-Classification-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Equal Interval Classification<\/strong>: <em>[cartography]<\/em> The equal interval classification method divides attribute values into equal size ranges such as 0-20, 21-40, 41-60, 61-80, and 81-100. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"156\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/02\/ERDAS-Imagine-Tokyo-300x156.jpg\" alt=\"ERDAS Imagine Tokyo\" class=\"wp-image-96535\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/02\/ERDAS-Imagine-Tokyo-300x156.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/02\/ERDAS-Imagine-Tokyo-678x353.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/02\/ERDAS-Imagine-Tokyo-768x399.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/02\/ERDAS-Imagine-Tokyo.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Earth Resources Data Analysis System (ERDAS) Imagine<\/strong>: <em>[software]<\/em> ERDAS Imagine is a leading remote sensing software owned by Hexagon Geospatial. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/01\/esri-toolbox-150x100.png\" alt=\"esri toolbox\" class=\"wp-image-21787\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/01\/esri-toolbox-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/01\/esri-toolbox-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/01\/esri-toolbox-115x78.png 115w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Esri (Environmental Systems Research Institute)<\/strong>: <em>[software]<\/em> Esri is the largest global supplier and developer of GIS software based in Redlands, California.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"F\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">F<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Facet-150x100.png\" alt=\"Facet\" class=\"wp-image-4594\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Facet<\/strong>: <em>[data structure]<\/em> A facet is a triangular face in a Triangular Irregular Network (TIN). TINs are three-dimensional coordinates depicting elevation surfaces. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/UTM_Zones-150x100.jpg\" alt=\"UTM Zones (False Northing, False Easting)\" class=\"wp-image-4596\"\/><\/figure>\n<\/div>\n\n\n<p><strong>False northing<\/strong>: <em>[coordinate system]<\/em> A false northing is a number added in a map projection in the y direction to avoid negative coordinate locations within the specified area of that map projection. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-150x100.png\" alt=\"Feature\" class=\"wp-image-5303\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Feature.png 700w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Feature<\/strong>: <em>[data structure]<\/em> A feature is a cartographic point, line, or polygon object with a spatial location in the real-world landscape that can be used in a GIS for storage, visualization, and analysis. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-150x100.png\" alt=\"attribute field\" class=\"wp-image-5304\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/table-field.png 700w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Field (Attribute Table)<\/strong>: <em>[data structure]<\/em> An attribute field (or item) are characteristics used to describe each feature in a geographic data set usually viewed as columns in a table. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/US-FIPS-150x100.png\" alt=\"US FIPS\" class=\"wp-image-5312\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Federal Information Processing Standard (FIPS)<\/strong>: <em>[organization]<\/em> FIPS is a federal unique identifier code used to define political or physical features in the United States. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Flow-Direction-2-150x100.jpg\" alt=\"Flow Direction\" class=\"wp-image-4610\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Flow direction<\/strong>: <em>[GIS processing]<\/em> Flow direction calculates the direction water will flow using the slope from neighboring cells. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-150x100.png\" alt=\"Focal Operation Raster\" class=\"wp-image-4717\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-200x135.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-425x287.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2-230x155.png 230w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Focal-Operation-Raster-2.png 467w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Focal Operation<\/strong>: <em>[mathematics]<\/em> The focal operation is a spatial function that computes an output value of each cell using neighborhood values such as convolution, kernel, and moving windows. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"G\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">G<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-150x100.png\" alt=\"GDAL\" class=\"wp-image-5871\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/gdal.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>GDAL<\/strong>: <em>[GIS software]<\/em> Geospatial Data Abstraction Library (GDAL) is a C++ library for reading and writing raster geospatial data formats, implementing common GIS operations (unions, intersections, joins, clipping, etc.) with command line utilities.  <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Generalization-Tool-1-150x100.png\" alt=\"Generalization Tool\" class=\"wp-image-5313\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Generalization-Tool-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Generalization-Tool-1-50x32.png 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Generalization Tool<\/strong>: <em>[GIS processing]<\/em> The generalization tool is an editing process that simplifies the shapes by reducing the number of vertices in a line or polygon. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geocentric-150x100.png\" alt=\"Geocentric\" class=\"wp-image-5319\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Geocentric<\/strong>: <em>[geodesy]<\/em> Geocentric is a measuring system that uses the center of the Earth as its origin, such as the WGS 1984 datum.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geocoding-150x100.png\" alt=\"Geocoding\" class=\"wp-image-5315\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geocoding-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geocoding-50x32.png 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Geocoding<\/strong>: <em>[GIS processing]<\/em> Geocoding is the process of assigning geographic coordinates to places based on street address, town\/city, province\/state and country. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodesy-1-150x100.png\" alt=\"geodesy\" class=\"wp-image-5317\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodesy-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/geodesy-1-50x32.png 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Geodesy<\/strong>: <em>[GIS dictionary]<\/em> Geodesy (or Geodetics) is a branch of applied mathematics and earth science of locating and assigning three-dimensional points on Earth by measuring the shape of the Earth. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"200\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-300x200.png\" alt=\"geofence example diagram\" class=\"wp-image-40471\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-678x451.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-768x511.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-550x366.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-1265x842.png 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram-360x240.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/geofence-example-diagram.png 1376w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Geofencing<\/strong>: <em>[GIS dictionary]<\/em> A virtual geographic boundary designed to give real-time alerts and increase awareness. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geographic-Information-Systems-150x100.png\" alt=\"Geographic Information Systems\" class=\"wp-image-5320\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geographic-Information-Systems-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geographic-Information-Systems-50x32.png 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Geographic Information Systems (GIS)<\/strong>: <em>[GIS dictionary]<\/em> GIS is a computer-based tool that analyzes, stores, manipulates and visualizes geographic information on a map, good for finding spatial patterns, relationships and trends. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geoid-150x100.png\" alt=\"Geoid\" class=\"wp-image-5322\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geoid-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Geoid-50x32.png 50w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Geoid<\/strong>: <em>[geodesy]<\/em> A geoid is a measurement-based equipotential surface model of the shape of the Earth primarily used as a basis of assigning terrain height. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><style>.kb-image5501_41150a-2115.kb-image-is-ratio-size, .kb-image5501_41150a-2115 .kb-image-is-ratio-size{max-width:150px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image5501_41150a-2115.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image5501_41150a-2115 .kb-image-is-ratio-size{align-self:unset;}.kb-image5501_41150a-2115 figure{max-width:150px;}.kb-image5501_41150a-2115 .image-is-svg, .kb-image5501_41150a-2115 .image-is-svg img{width:100%;}.kb-image5501_41150a-2115 .kb-image-has-overlay:after{opacity:0.3;}.kb-image5501_41150a-2115 img.kb-img, .kb-image5501_41150a-2115 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}@media all and (max-width: 1024px){.kb-image5501_41150a-2115 img.kb-img, .kb-image5501_41150a-2115 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}}@media all and (max-width: 767px){.kb-image5501_41150a-2115 img.kb-img, .kb-image5501_41150a-2115 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}}<\/style>\n<div class=\"wp-block-kadence-image kb-image5501_41150a-2115\"><figure class=\"alignleft size-medium is-resized\"><img decoding=\"async\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/07\/Geomedia-Bar-Charts-300x160.jpg\" alt=\"Geomedia Bar Charts\" class=\"kb-img wp-image-96514\" width=\"150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/07\/Geomedia-Bar-Charts-300x160.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/07\/Geomedia-Bar-Charts-678x362.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/07\/Geomedia-Bar-Charts-768x410.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/07\/Geomedia-Bar-Charts.jpg 1000w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/figure><\/div>\n<\/div><\/div>\n\n\n\n<p><strong>Geomedia<\/strong>: <em>[software]<\/em> GeoMedia is a GIS software package produced by Hexagon Geospatial (previously Intergraph) used to analyze, store and visualize geographic data.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kb-image5501_51a27d-8312.kb-image-is-ratio-size, .kb-image5501_51a27d-8312 .kb-image-is-ratio-size{max-width:150px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image5501_51a27d-8312.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image5501_51a27d-8312 .kb-image-is-ratio-size{align-self:unset;}.kb-image5501_51a27d-8312 figure{max-width:150px;}.kb-image5501_51a27d-8312 .image-is-svg, .kb-image5501_51a27d-8312 .image-is-svg img{width:100%;}.kb-image5501_51a27d-8312 .kb-image-has-overlay:after{opacity:0.3;}.kb-image5501_51a27d-8312 img.kb-img, .kb-image5501_51a27d-8312 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}@media all and (max-width: 1024px){.kb-image5501_51a27d-8312 img.kb-img, .kb-image5501_51a27d-8312 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}}@media all and (max-width: 767px){.kb-image5501_51a27d-8312 img.kb-img, .kb-image5501_51a27d-8312 .kb-img img{border-top:1px solid var(--global-palette6, #718096);border-right:1px solid var(--global-palette6, #718096);border-bottom:1px solid var(--global-palette6, #718096);border-left:1px solid var(--global-palette6, #718096);}}<\/style>\n<div class=\"wp-block-kadence-image kb-image5501_51a27d-8312\"><figure class=\"alignleft size-medium\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"155\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Global-Mapper-Software-300x155.jpg\" alt=\"Blue Marble Global Mapper Software\" class=\"kb-img wp-image-96872\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Global-Mapper-Software-300x155.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Global-Mapper-Software-678x351.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Global-Mapper-Software-768x397.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Global-Mapper-Software.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure><\/div>\n\n\n\n<p><strong>Global Mapper<\/strong>: <em>[software]<\/em> Global Mapper is a commercial GIS software product for spatial analysis and visualization. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-150x100.png\" alt=\"Global Operation Raster\" class=\"wp-image-4720\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-200x135.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-425x287.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster-230x155.png 230w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Global-Operation-Raster.png 467w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Global Operation<\/strong>: <em>[mathematics]<\/em> A global operation is a process or function that is performed on each output cell using all of the cells of the input raster. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-150x100.png\" alt=\"Gnomonic Projection\" class=\"wp-image-5324\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-768x512.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-550x366.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Gnomonic-Projection.png 800w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Gnomonic Projection<\/strong>: <em>[map projection]<\/em> A Gnomonic projection uses the center of the spheroid as the projection center. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/grass-gis3-150x100.jpg\" alt=\"GRASS GIS Desktop\" class=\"wp-image-4023\"\/><\/figure>\n<\/div>\n\n\n<p><strong>GRASS GIS<\/strong>: <em>[software]<\/em> GRASS GIS (Geographic Resource Analysis Support System) is an open source GIS software package, highly used in academic institutions with over 400 modules for GIS analysis. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Ellipsoid-150x100.png\" alt=\"Ellipsoid Graticules\" class=\"wp-image-4562\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Graticule<\/strong>: <em>[coordinate system]<\/em> Graticules are lines of latitude or longitude on a digital or hard copy map and assist in showing the geographic locations of map features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Prime-Meridian-150x100.png\" alt=\"Prime Meridian\" class=\"wp-image-5325\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Greenwich Meridian (Prime Meridian)<\/strong>: <em>[coordinate system]<\/em> The Greenwich meridian passes through the Royal Observatory in Greenwich, England, and is defined as a 0\u00b0 line of longitude.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Axis-Spheroid-150x100.png\" alt=\"Axis Spheroid\" class=\"wp-image-5326\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Geodetic Reference System 1980 (GRS 80)<\/strong>: <em>[geodesy]<\/em> GRS80 is a geodetic reference system consisting of a global reference ellipsoid and a gravity field model (geoid). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"H\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">H<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"129\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-300x129.jpg\" alt=\"National Geodetic Survey Explorer\" class=\"wp-image-96224\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-300x129.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-678x292.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer-768x331.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/10\/National-Geodetic-Survey-Explorer.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Horizontal Datum<\/strong>: <em>[geodesy]<\/em> A horizontal datum provides a frame of reference as a basis for placing locations at a specific latitude and longitude points on the spheroid. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Hydrography-150x100.png\" alt=\"Hydrography\" class=\"wp-image-5329\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Hydrography<\/strong>: <em>[GIS dictionary]<\/em> Hydrography is a term describing the geographic representation of water features such as streams, rivers, and lakes. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Hypsography-150x100.png\" alt=\"Hypsography\" class=\"wp-image-5331\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Hypsography<\/strong>: <em>[ GIS dictionary ]<\/em> Hypsography is the geographic representation of features on a map related to elevation, altitude, and height above sea level from a reference surface. (Hypso is Greek for height). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"I\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">I<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"133\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/IDRISI-Segmentation-300x133.jpg\" alt=\"IDRISI Segmentation\" class=\"wp-image-96207\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/IDRISI-Segmentation-300x133.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/IDRISI-Segmentation-678x301.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/IDRISI-Segmentation-768x341.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/IDRISI-Segmentation.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Idrisi<\/strong>: <em>[software]<\/em> Idrisi is a GIS\/remote sensing software package developed by Clark Laboratories in 1987, widely used in the education system. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Land-Surface-Temperature-April-2015-150x100.png\" alt=\"Land Surface Temperature April 2015\" class=\"wp-image-4728\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Inverse Distance Weighted (IDW) Interpolation<\/strong>: <em>[mathematics]<\/em> IDW interpolation is a technique used to estimate values of unsampled locations based on the value and distance of known, sampled locations. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-150x100.png\" alt=\"IKONOS\" class=\"wp-image-5333\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/IKONOS.png 450w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>IKONOS<\/strong>: <em>[remote sensing]<\/em> IKONOS is a high-resolution commercial imaging satellite that provides 1-meter panchromatic and 3-meter multispectral (blue, green, red, near-infrared) imagery.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-150x100.png\" alt=\"near-infrared\" class=\"wp-image-5336\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/near-infrared.png 350w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Infrared<\/strong>: <em>[remote sensing]<\/em> An infrared image represents reflectance grid cells that are recorded in the near-infrared wavelengths, typically 0.7 to 1.1 micrometers.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-150x100.png\" alt=\"interpolation\" class=\"wp-image-5337\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/interpolation.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Interpolation<\/strong>: <em>[mathematics]<\/em> Interpolation is the estimation of unsampled locations based on known location sampled values such as elevation, temperature, and other predicted variables. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-150x100.png\" alt=\"Intersect\" class=\"wp-image-5338\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-678x451.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-768x511.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-550x366.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-850x566.png 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/intersect-1.png 900w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Intersect Tool (Overlay)<\/strong>: <em>[GIS processing]<\/em> The intersect tool uses two inputs and restricts the output geometry similar to a clip by preserving the attributes in both input layers.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"K\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">K<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-150x100.png\" alt=\"Kriging\" class=\"wp-image-5340\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/kriging.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Kriging<\/strong>: <em>[GIS processing]<\/em> Kriging is a statistical interpolation technique that uses known location values to interpolate values at unknown locations and also estimates standard error and uncertainty. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"L\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">L<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-150x100.png\" alt=\"Land Information System\" class=\"wp-image-5345\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Land-Information-System.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Land Information System (LIS)<\/strong>: <em>[GIS dictionary definition]<\/em> LIS was a name originally applied for GIS systems specifically developed for property ownership and boundary records management. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-150x100.png\" alt=\"Landsat\" class=\"wp-image-5349\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image.png 400w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-115x76.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Landsat-Image-233x155.png 233w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Landsat<\/strong>: <em>[remote sensing]<\/em> Landsat consists of 8 satellite missions spanning more than 4 decades with space-borne remote sensing capabilities for scanning land resources.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Latitudes-150x100.png\" alt=\"Latitude Coordinates\" class=\"wp-image-4955\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Latitude<\/strong>: <em>[coordinate system]<\/em> Latitudes are spherical coordinates of Earth locations that vary in north-south directions ranging from 0\u00b0 at the Equator to 90\u00b0 (North or South) at the poles.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/01\/lidar-point-cloud-150x100.png\" alt=\"lidar point cloud\" class=\"wp-image-2990\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Light Detection and Ranging (LiDAR)<\/strong>: <em>[remote sensing]<\/em> LiDAR uses laser pulse measurements to identify heights, depths, and other properties of features on the Earth\u2019s surface.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Local-Operation-Raster-150x100.png\" alt=\"Local Operation\" class=\"wp-image-5355\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Local Operator<\/strong>: <em>[GIS processing]<\/em> A local operation is a spatial operation where the output extent is limited to the same location as the input such as arithmetic, statistical, relational, trigonometric, exponential, and logarithmic operations.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/locator-map-150x100.png\" alt=\"locator map\" class=\"wp-image-5357\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Locator Map<\/strong>: <em>[cartography]<\/em> Locator maps show the extent of the primary map in relation to a larger extent area giving context to the map reader to gain a better understanding of the overall area.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-150x100.png\" alt=\"Longitudes\" class=\"wp-image-5358\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Longitude-Dictionary.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Longitude<\/strong>: <em>[coordinate system]<\/em> Longitudes are coordinate on Earth in east-west directions ranging from 0\u00b0 to +180\u00b0 east and \u2212180\u00b0 west.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"M\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">M<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-150x100.png\" alt=\"Magnetic North Pole\" class=\"wp-image-5359\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Magnetic-North-Pole.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Magnetic North Pole<\/strong>: <em>[geodesy]<\/em> The magnetic north is a point in Northern Canada where the northern lines of attraction enter the Earth and which compass needles orient in direction. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/ManifoldSystem-150x100.png\" alt=\"Manifold System\" class=\"wp-image-4077\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Manifold GIS<\/strong>: <em>[software]<\/em> Manifold is a GIS software package used for mapping with a focus on speed in analysis and visualization. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Algebra-150x100.png\" alt=\"Map Algebra\" class=\"wp-image-5361\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Map Algebra<\/strong>: <em>[mathematics]<\/em> Map algebra is the combination of spatial data using mathematical, statistical, and trigonometric operations to generate new raster outputs. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-150x100.png\" alt=\"Map Legend\" class=\"wp-image-5363\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Map-Legend.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Map Legend<\/strong>: <em>[cartography]<\/em> A map legend is a visual graphic of the symbology used in a map that tells the map reader what polygons, lines, points, or grid cells represent.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Map-Projection-Georeference-150x100.png\" alt=\"Map Projection Georeference\" class=\"wp-image-5135\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Map Projection<\/strong>: <em>[cartography]<\/em> A map projection is a systematic rendering of features that transforms a 3D ellipsoid or spheroid of Earth into a 2D map surface with some distortion.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized has-custom-border\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"160\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/02\/MapInfo-Professional-World-300x160.jpg\" alt=\"MapInfo Professional World\" class=\"has-border-color has-theme-palette-6-border-color wp-image-97156\" style=\"border-width:1px;width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/02\/MapInfo-Professional-World-300x160.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/02\/MapInfo-Professional-World-678x362.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/02\/MapInfo-Professional-World-768x410.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/02\/MapInfo-Professional-World.jpg 1366w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>MapInfo<\/strong>: <em>[software]<\/em> MapInfo by Precisely (founded in 1986) is a GIS location intelligence suite that allows users to manage, view, and create geospatial data.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-150x100.png\" alt=\"Lines of Longitude\" class=\"wp-image-4734\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-538x360.png 538w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Meridian<\/strong>: <em>[coordinate system]<\/em> Meridians are lines of longitude that vary in east-west directions ranging from 0\u00b0 to +180\u00b0 east and \u2212180\u00b0 west.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-150x100.png\" alt=\"Metadata\" class=\"wp-image-5365\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Metadata.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Metadata<\/strong>: <em>[data structure]<\/em> Metadata is data that describes data such as the date, abstract, coordinate system, attribute information, origin, and accuracy. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"360\" height=\"120\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels.png\" alt=\"Raster Pixels\" class=\"wp-image-20727\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels-300x100.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels-50x17.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels-200x67.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/Raster-Pixels-115x38.png 115w\" sizes=\"auto, (max-width: 360px) 100vw, 360px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Minimum Mapping Unit<\/strong>: <em>[remote sensing]<\/em> A minimum mapping unit is the smallest resolution area when interpreting remotely-seemed satellite or aerial imagery.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-150x100.jpg\" alt=\"MODIS Iceland\" class=\"wp-image-5369\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-150x100.jpg 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-300x200.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-50x33.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-200x133.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-425x283.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-550x367.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-115x77.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland-233x155.jpg 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/modis-iceland.jpg 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Moderate Resolution Imaging Sensor (MODIS)<\/strong>: <em>[remote sensing]<\/em> MODIS is a high spectral resolution and moderate spatial resolution (250-1000 meters) imaging scanner.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-150x100.png\" alt=\"Moving Window\" class=\"wp-image-5370\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Moving Window<\/strong>: <em>[mathematics]<\/em> A moving window is a rectangular arrangement of cells that applies an operation to each cell in a raster dataset while shifting in a position entirely.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-150x100.png\" alt=\"Multispectral example\" class=\"wp-image-5371\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Multispectral-Example.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Multispectral Imagery<\/strong>: <em>[remote sensing]<\/em> A multispectral image had several channels consisting of several spectral bands of wavelengths such as red, green, blue, and NIR.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"N\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">N<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-150x100.png\" alt=\"Nadir\" class=\"wp-image-5373\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nadir.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Nadir<\/strong>: <em>[remote sensing]<\/em> Nadir is the point directly below the aircraft which is usually near the center of the aerial image.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-150x100.png\" alt=\"National Land Cover Dataset\" class=\"wp-image-5375\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/national-land-cover-dataset.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>National Land Cover Dataset (NLCD)<\/strong>: <em>[organization]<\/em> The NLCD is a Landsat Thematic Mapper (TM) based classification of land cover in the United States. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"144\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/11\/NOAA-NowCoast-300x144.jpg\" alt=\"NOAA NowCoast\" class=\"wp-image-97123\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/11\/NOAA-NowCoast-300x144.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/11\/NOAA-NowCoast-678x326.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/11\/NOAA-NowCoast-768x369.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/11\/NOAA-NowCoast.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>National Oceanic and Atmospheric Administration (NOAA)<\/strong>: <em>[organization]<\/em> NOAA is the US government agency that oversees the development of national datums and several weather and ocean satellites. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-150x100.png\" alt=\"Wetland Aerial\" class=\"wp-image-5485\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wetland-Aerial.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>National Wetlands Inventory (NWI)<\/strong>: <em>[organization]<\/em> The NWI is a dataset compiled by the US Fish and Wildlife Services that describes the type and extent of wetlands in North America. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-150x100.png\" alt=\"Nearest Neighbor Interpolation\" class=\"wp-image-5379\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nearest-Neighbor-Interpolation.png 350w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Nearest Neighbor Interpolation<\/strong>: <em>[mathematics]<\/em> Nearest neighbor interpolation involves taking the output value from the nearest input layer cell center, commonly used for discrete data like land covers. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-150x100.png\" alt=\"Neat Line\" class=\"wp-image-5381\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-678x454.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-768x514.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-850x569.png 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Neat-Line.png 900w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Neat Line<\/strong>: <em>[cartography]<\/em> A neat line is a solid border cartographic element that surrounds all the data, legend, scale, and other features helping the map readers focus on the inner details in a map. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-150x100.png\" alt=\"Moving Window\" class=\"wp-image-5370\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Moving-Window-1.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Neighborhood Operation<\/strong>: <em>[mathematics]<\/em> A neighborhood operation is a spatial function where the output location, area, and extent come from areas larger than and adjacent to the input cells. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-150x100.png\" alt=\"GIS Network\" class=\"wp-image-5415\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Network-GIS-1.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Network<\/strong>: <em>[data structure]<\/em> A network in GIS is a connected set of line features used to model for and demand through real-world networks such as rivers and roads. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-150x100.png\" alt=\"Node GIS\" class=\"wp-image-5420\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Node-GIS.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Node<\/strong>: <em>[data structure]<\/em> A node is an important point along a line feature where two lines intersect. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-150x100.png\" alt=\"Nominal Scale\" class=\"wp-image-5388\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-678x454.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Nominal-Scale-1.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Nominal Scale<\/strong>: <em>[cartography]<\/em> A nominal scale is a type of measurement that indicates the difference between classes or categories of data. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-150x100.png\" alt=\"survey equipment\" class=\"wp-image-5390\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-678x454.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>North American Datum 1927 (NAD27)<\/strong>: <em>[geodesy]<\/em> NAD27 is the adjustment of long-baseline surveys to establish a network of standardized horizontal positions in North America using the Clarke Ellipsoid of 1866 and a fixed center at Meade\u2019s Ranch, Kansas. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"161\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NAD83-NOAA-Control-Stations-300x161.jpg\" alt=\"NAD83 NOAA Control Stations\" class=\"wp-image-96257\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NAD83-NOAA-Control-Stations-300x161.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NAD83-NOAA-Control-Stations-678x363.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NAD83-NOAA-Control-Stations-768x411.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NAD83-NOAA-Control-Stations.jpg 1003w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>North American Datum of 1983 (NAD83)<\/strong>: <em>[geodesy]<\/em> NAD83 is the successor of NAD27 that creates a set of standard horizontal positions for North America based on the reference ellipsoid GRS80. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-150x100.png\" alt=\"NAVD29\" class=\"wp-image-5392\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-550x369.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/NAVD29.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>North American Vertical Datum of 1929 (NAVD29)<\/strong>: <em>[geodesy]<\/em>  NAVD29 or National Geodetic Vertical Datum of 1929 (NGVD29) gives a vertical measurement network reference frame for which vertical elevations and depressions can be based in North America. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/navd88-150x100.png\" alt=\"NAVD88\" class=\"wp-image-5394\"\/><\/figure>\n<\/div>\n\n\n<p><strong>North American Vertical Datum of 1988 (NAVD88)<\/strong>: <em>[geodesy]<\/em> NAVD88 is a vertical datum that provides a reference surface in which vertical heights (altitude) and depth (depression) above and below mean sea level is measured. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-150x100.png\" alt=\"North Arrow Examples\" class=\"wp-image-5396\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-550x369.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/North-Arrow-Examples.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>North Arrow<\/strong>: <em>[cartography]<\/em> A north arrow provides an orientation to the map reader by showing the north direction as a graphical depiction. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Northing-150x100.png\" alt=\"Northing\" class=\"wp-image-5397\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Northing<\/strong>: <em>[coordinate system]<\/em> A northing is the axis in the approximate north-south direction (or y-value) in UTM and other standard coordinate systems. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"O\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">O<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"159\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/11\/OBIA-Cover-300x159.jpg\" alt=\"OBIA Cover\" class=\"wp-image-96116\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/11\/OBIA-Cover-300x159.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/11\/OBIA-Cover-678x360.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/11\/OBIA-Cover-768x408.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/11\/OBIA-Cover.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Object Based Image Analysis (OBIA)<\/strong>: <em>[remote sensing]<\/em> OBIA is an image classification technique that segments images and classifies them using spectral, spatial, and relational properties and characteristics. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-150x100.png\" alt=\"Ordinal Scale\" class=\"wp-image-5399\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-678x454.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-768x515.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-550x369.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/ordinal.png 800w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Ordinal Scale<\/strong>: <em>[coordinate system]<\/em> An ordinal scale represents the relative order of values but does not record the magnitude of differences between values. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Datum-150x100.png\" alt=\"Orthographic\" class=\"wp-image-4529\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Orthographic Projection<\/strong>: <em>[map projection]<\/em> An orthographic projection is a map projection that represents 3D data in 2D where all the projection lines are orthogonal to the projection plane. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-150x100.png\" alt=\"Orthometric Height\" class=\"wp-image-5400\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Orthometric-Height.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Orthometric Height<\/strong>: <em>[map projection]<\/em> Orthometric height is a height measured from the Geoid surface to a point on the surface of the Earth. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-150x100.png\" alt=\"Overshoot\" class=\"wp-image-4784\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-200x135.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-425x287.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot-230x155.png 230w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Overshoot.png 467w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Overshoot<\/strong>: <em>[editing]<\/em> An overshoot is a digitized line that extends past the intended line of connection. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"P\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">P<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-150x100.png\" alt=\"Panchromatic Image\" class=\"wp-image-5402\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-678x455.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-550x369.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Panchromatic-Image-1.png 700w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Panchromatic Image<\/strong>: <em>[editing]<\/em> A panchromatic image records wavelengths in only one wider range band resulting in grayscale images. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-150x100.png\" alt=\"Parallax\" class=\"wp-image-5405\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-678x455.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-425x285.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-550x369.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Parallax.png 700w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Parallax <\/strong>: <em>[remote sensing]<\/em> Parallax measures the apparent shift in relative positions of Earth features when it is viewed in different locations. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/passive-satellite-150x100.png\" alt=\"Passive satellites\" class=\"wp-image-2698\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Passive Sensors<\/strong>: <em>[remote sensing]<\/em> Passive sensors measure natural energy from the sun as reflected sunlight or thermal radiation such as Landsat, SPOT, and GeoEye. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-150x100.png\" alt=\"Pixels (GIS)\" class=\"wp-image-5406\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Pixels-GIS.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Pixels (GIS)<\/strong>: <em>[data structure]<\/em> Pixels are the grid cells that make up raster images, which are identical in size. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-150x100.png\" alt=\"Planar Topology\" class=\"wp-image-5407\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Planar Topology<\/strong>: <em>[editing]<\/em> Planar topology requires that intersections for lines and polygons in a digital data layer are enforced and that no two lines or polygons cross. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-150x100.png\" alt=\"Polygons\" class=\"wp-image-5408\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Polygons.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Polygon<\/strong>: <em>[data structure]<\/em> A polygon is a closed, connected set of lines that defines a geographic boundary with an area and perimeter such as lakes, forests, and country boundaries. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-150x100.png\" alt=\"GPS PDOP\" class=\"wp-image-5409\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-PDOP.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Positional Dilution of Precision (PDOP)<\/strong>: <em>[data structure]<\/em> PDOP is a quantitative measurement used to represent the quality of the satellite geometry when taking GPS readings. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-150x100.png\" alt=\"Public Land Survey System\" class=\"wp-image-5411\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Public-Land-Survey-System.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Public Land Survey System (PLSS)<\/strong>: <em>[organization]<\/em> The <a href=\"https:\/\/gisgeography.com\/public-land-survey-system-plss\/\">PLSS<\/a> is a land measurement system used in the western United States to define parcel boundaries and locations. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"Q\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Q<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"154\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/04\/QGIS-Desktop-300x154.jpg\" alt=\"QGIS Desktop\" class=\"wp-image-96210\" style=\"width:140px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/04\/QGIS-Desktop-300x154.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/04\/QGIS-Desktop-678x348.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/04\/QGIS-Desktop-768x395.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/04\/QGIS-Desktop.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>QGIS<\/strong>: <em>[software]<\/em> QGIS (formerly Quantum GIS) is a free and open source software package that allows you to create, edit, visualize, analyze and publish geospatial information. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-150x100.png\" alt=\"Quadtree\" class=\"wp-image-5416\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quadtree.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Quad-Trees<\/strong>: <em>[remote sensing]<\/em> Quad-Trees are raster data structures based on successive reduction of homogeneous cells for the purpose of reducing storage requirements. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-150x100.png\" alt=\"Quantile Classification\" class=\"wp-image-5417\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Quantile-Classification.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Quantile Classification<\/strong>: <em>[cartography]<\/em> Quantile classification is a classification method that divides classes so that the total number of features in each class is approximately the same. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-150x100.png\" alt=\"GIS query\" class=\"wp-image-5418\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-678x452.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/query.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Query<\/strong>: <em>[programming]<\/em> A query is a request or search of spatial or tabular data based on user-defined criteria, resulting in a subset of selected records. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"R\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">R<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-150x100.png\" alt=\"Random Sample\" class=\"wp-image-5421\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Random-Sample.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Random Location Sampling<\/strong>: <em>[statistics]<\/em> Random location sampling is a statistical technique where sample locations are selected by a random process with minimal biases. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-150x100.png\" alt=\"Raster Grid\" class=\"wp-image-5424\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Raster-Grid.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Raster Data<\/strong>: <em>[data structure]<\/em> A raster is a data model used in GIS which is usually regularly-size rectangular or square shaped grid cells arranged in rows in columns. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/Raster-Resample-150x100.png\" alt=\"Raster Resample\" class=\"wp-image-12047\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Raster Resampling<\/strong>: <em>[mathematics]<\/em> Raster resampling is a technique used to recalculate and assign new cell values when adjusting the cell size or orientation of a raster grid. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-150x100.png\" alt=\"Attribute Table Record\" class=\"wp-image-5425\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Attribute-Table-Record.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Record<\/strong>: <em>[data structure]<\/em> A record is an attribute table row that specifies an instance or spatial feature of an entity. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/california-natural-data-150x100.png\" alt=\"Registration\" class=\"wp-image-1090\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Registration <\/strong>: <em>[GIS processing]<\/em> Registration is the alignment or assignment of coordinates from a non-projected coordinate system to a coordinate system. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-150x100.png\" alt=\"Remote Sensing\" class=\"wp-image-5428\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Remote-Sensing.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Remote Sensing<\/strong>: <em>[GIS dictionary definition]<\/em> Remote sensing is the science of obtaining information about the Earth without physically being there, such as by satellite, unmanned aerial vehicle and aircraft. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-150x100.png\" alt=\"Rubbersheet\" class=\"wp-image-5427\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Rubbersheet.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Rubbersheeting <\/strong>: <em>[mathematics]<\/em> Rubbersheeting is a transformation technique using polynomial or other non-linear functions to match feature geometry. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-150x100.png\" alt=\"affine rotate\" class=\"wp-image-11002\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-rotate.png 450w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Rotate<\/strong>: <em>[mathematics]<\/em> Rotation is an affine transformation that changes polylines, polygons in a plane by changing the angle with a pivot location. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"S\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">S<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-150x100.png\" alt=\"Scalebar\" class=\"wp-image-5429\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Scalebar.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Scale Bar<\/strong>: <em>[mathematics]<\/em> A scale bar graphically shows the proportional distance on the map with units such as kilometers or meters. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-150x100.png\" alt=\"affine scale\" class=\"wp-image-11003\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-scale.png 450w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Scale<\/strong>: <em>[mathematics]<\/em> An affine transformation changes points, polylines, polygons in a plane by scaling, rotating, skewing, or translating coordinates in two or three-dimensional spaces. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-150x100.png\" alt=\"Selection Tool\" class=\"wp-image-5431\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Selection-Tool.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Selection Tool<\/strong>: <em>[GIS processing]<\/em> The selection tool identifies an object or set of objects based on user-selected criteria and properties, typically with Structured Query Language (SQL). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Semi-Minor-Axis-150x100.png\" alt=\"Semi-Minor Axis\" class=\"wp-image-4815\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Semi-Major\/Minor Axis<\/strong>: <em>[geodesy]<\/em> The semi-major axis is one-half of the major axis that is the larger of the two radial axes that define an ellipsoid. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-150x100.png\" alt=\"Semi-Variance\" class=\"wp-image-5433\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Semi-Variance.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Semivariance<\/strong>: <em>[statistics]<\/em> Semivariance is the variance between valued samples given an inter-sample distances known as lag. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-150x100.png\" alt=\"Servers\" class=\"wp-image-5436\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Servers.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Server<\/strong>: <em>[hardware]<\/em> A server is a computer component that offers data storage and organization providing subsets of GIS data in response to user requests. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-150x100.png\" alt=\"set algebra\" class=\"wp-image-5440\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/set-algebra.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Set Algebra<\/strong>: <em>[mathematics]<\/em> Set algebra is a method to select items in a database based on operators such as &#8220;greater than&#8221;, &#8220;less than&#8221;, &#8220;equal to&#8221; or \u2018not equal to\u2019 using command lines such as SQL. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-150x100.png\" alt=\"Shaded Relief\" class=\"wp-image-5441\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Shaded-Relief.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Shaded Relief<\/strong>: <em>[remote sensing]<\/em> A shaded relief map displays the brightness and shadows of terrain reflection given a sun angle and direction of sunlight. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-150x100.png\" alt=\"Sidelap Endlap\" class=\"wp-image-5442\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Sidelap-Endlap.png 550w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Sidelap<\/strong>: <em>[remote sensing]<\/em> Sidelap (or side overlap) consists of the overlapping edge areas of photographs between adjacent flight lines. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-150x100.png\" alt=\"Skeletonize\" class=\"wp-image-5443\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Skeletonize-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Skeletonize<\/strong>: <em>[GIS processing]<\/em> Skeletonizing is the process of thinning a raster line to a single pixel width, typically for conversion to vector data format. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-150x100.png\" alt=\"affine skew\" class=\"wp-image-11004\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/06\/affine-skew.png 450w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Skew<\/strong>: <em>[mathematics]<\/em> Skewing distorts a feature by arranging its vertices in the x or y-direction. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-150x100.png\" alt=\"Sliver\" class=\"wp-image-4825\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-200x135.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-425x287.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver-230x155.png 230w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Sliver.png 467w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Sliver<\/strong>: <em>[editing]<\/em> A sliver is a small, spurious gap between polygons often considered as a topology error from imprecise digitization of features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-150x100.png\" alt=\"Slope\" class=\"wp-image-5445\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1.png 400w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Slope-1-232x155.png 232w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Slope<\/strong>: <em>[mathematics]<\/em> Slope is the change in elevation or steepness with respect to change in location measured in degrees or percent slope. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-150x100.png\" alt=\"Snapping Environment\" class=\"wp-image-5446\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Snapping-Environment.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Snapping Environment<\/strong>: <em>[editing]<\/em> Snapping determines the distance that newly digitized points, lines, and polygons will occupy the same location as existing features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-150x100.png\" alt=\"SSURGO \" class=\"wp-image-5447\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Soil Survey Geographic Database (SSURGO)<\/strong>: <em>[organization]<\/em> SSURGO is a fine-scale, county-level, soil survey database prepared by the National Resource Conservation Service. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-150x100.png\" alt=\"Spaghetti Data Model \" class=\"wp-image-5448\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spaghetti-Data-Model-1.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Spaghetti Data Model<\/strong>: <em>[data structure]<\/em> The spaghetti data model is a simple and dated GIS model where lines may cross without intersecting or topology without attributes. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-150x100.png\" alt=\"Spatial Relationship\" class=\"wp-image-5450\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spatial-Relationship.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Spatial Relationship<\/strong>: <em>[data structure]<\/em> A spatial relationship that links features geographically with a table by a unique identifier. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-150x100.png\" alt=\"Spherical Coorinates\" class=\"wp-image-5451\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spherical-Coorinates.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Spherical Coordinates<\/strong>: <em>[coordinate system]<\/em> Spherical coordinates is a coordinate system based on a sphere defined by two angles of rotation in orthogonal planes such as latitudes and longitudes in a geographic coordinate system. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-150x100.png\" alt=\"Spheroid\" class=\"wp-image-5452\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spheroid.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Spheroid<\/strong>: <em>[geodesy]<\/em> A spheroid is a three-dimensional mathematical model representing the shape of the Earth based on the equation of a sphere. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-150x100.png\" alt=\"Spline Interpolation\" class=\"wp-image-5454\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Spline-Interpolation.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Spline<\/strong>: <em>[mathematics]<\/em> A spline is an interpolation method that generates a smooth surface by using multiple constrained polynomial functions minimizing the overall surface curvature. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-150x100.png\" alt=\"State Plane Coordinates\" class=\"wp-image-5455\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/State-Plane.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>State Plane Coordinates<\/strong>: <em>[coordinate system]<\/em> State Plane Coordinates is a standardized system in the United States based on Lambert conformal conic and transverse Mercator projections. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-150x100.png\" alt=\"SSURGO\" class=\"wp-image-5447\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SSURGO-1.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>State Soil Geographic (STATSGO)<\/strong>: <em>[organization]<\/em> STATSGO is a coarse resolution digital soil dataset from detailed and derived soil survey maps. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-150x100.png\" alt=\"Stereo Pairs\" class=\"wp-image-5457\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereo-Pairs.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Stereo Pairs<\/strong>: <em>[remote sensing]<\/em> Stereo pairs are overlapping photos taken at different positions that have parallax. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-150x100.png\" alt=\"Stereographic Projection\" class=\"wp-image-5458\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Stereographic-Projection-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Stereographic Projection<\/strong>: <em>[map projection]<\/em>  A stereographic projection is a mapping function that projects an entire sphere on a plane, except at the projection point. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-150x100.png\" alt=\"SQL\" class=\"wp-image-5459\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/SQL.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Structured Query Language (SQL)<\/strong>: <em>[map projection]<\/em> SQL is a set of commands used to manage data stored in relational database management systems (RDBMS). <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-150x100.png\" alt=\"survey equipment\" class=\"wp-image-5390\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-300x201.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-678x454.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-425x284.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-550x368.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment-232x155.png 232w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/survey-equipment.png 750w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Survey Station<\/strong>: <em>[surveying]<\/em> Survey stations are positions where surveys are performed during land surveys. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-150x100.png\" alt=\"Systematic Sampling\" class=\"wp-image-5460\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Systematic-Sampling-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Systematic Sampling<\/strong>: <em>[statistics]<\/em> Systematic sampling involves selecting samples using a regular and ordered sampling framework. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/spot1-header-150x100.jpg\" alt=\"SPOT-1\" class=\"wp-image-3926\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Syst\u00e8me Pour l\u2019Observation de la Terre (SPOT) Satellites<\/strong>: <em>[remote sensing]<\/em> <a href=\"https:\/\/gisgeography.com\/spot-satellite-pour-observation-terre\/\">SPOT satellites<\/a> are a group of French high resolution optical imaging Earth observation satellite which has been in operation for nearly 35 years. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"T\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">T<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"161\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NOAA-Control-Station-2-300x161.jpg\" alt=\"NOAA Control Station\" class=\"wp-image-96259\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NOAA-Control-Station-2-300x161.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NOAA-Control-Station-2-678x363.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NOAA-Control-Station-2-768x411.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/NOAA-Control-Station-2.jpg 1003w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Terrestrial Reference System<\/strong>: <em>[geodesy]<\/em> The terrestrial reference system is a set of measured points used to define a geodetic datum. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-150x100.png\" alt=\"Thematic Layers GIS\" class=\"wp-image-5463\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Thematic-Layers-GIS.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Thematic Layer<\/strong>: <em>[data structure]<\/em> A thematic layer is a distinct spatial entity in a data layer that is usually delineated as points, lines, and polygons. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"200\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Thematic-Mapper-300x200.jpg\" alt=\"Thematic Mapper\" class=\"wp-image-96252\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Thematic-Mapper-300x200.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Thematic-Mapper.jpg 600w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Thematic Mapper (TM)<\/strong>: <em>[remote sensing]<\/em> The Thematic Mapper is a high-resolution scanner on Landsat satellites (Landsat 4 and 5) that collects images in visible, near infrared, mid infrared, and thermal bands of the EM spectrum. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/03\/MicroImages-150x100.png\" alt=\"MicroImages\" class=\"wp-image-4115\"\/><\/figure>\n<\/div>\n\n\n<p><strong>TNTmips<\/strong>: <em>[software]<\/em> TNTmips is a GIS software application produced by Microimages that specializes in image manipulation and vector processing. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"204\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-300x204.jpg\" alt=\"Topographic Relief Map\" class=\"wp-image-90756\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-300x204.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-200x136.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-425x289.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-550x374.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-115x78.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map-360x245.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2024\/03\/Topographic-Relief-Map.jpg 610w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Topography<\/strong>: <em>[software]<\/em> Topography is the study and mapping of Earth\u2019s features including land surfaces, relief, natural, and constructed features. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-150x100.png\" alt=\"TIGER webmap\" class=\"wp-image-5465\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIGER-webmap.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Topologically Integrated Geographic Encoding and Referencing (TIGER)<\/strong>: <em>[organization]<\/em> TIGER is the central hub for United States census data with an inventory of other spatial data related to rivers, lakes, buildings, cities, political areas, and roads. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-150x100.png\" alt=\"Planar Topology\" class=\"wp-image-5407\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-300x202.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-200x134.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-425x286.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-550x370.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology-231x155.png 231w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Planar-Topology.png 650w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Topology<\/strong>: <em>[editing]<\/em> Topology is a set of rules that dictates the spatial properties of point, line, and area features such as connectivity, adjacency and contiguity. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-150x100.png\" alt=\"Traverse\" class=\"wp-image-5466\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Traverse.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Traverse<\/strong>: <em>[surveying]<\/em> A traverse is a set of survey stations spanning along a survey and are closed when returning to a starting point. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-150x100.png\" alt=\"Triangular Irregular Network (TIN)\" class=\"wp-image-4593\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-200x135.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-425x287.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/TIN.png 500w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Triangular Irregular Networks (TIN)<\/strong>: <em>[data structure]<\/em> TINs are vector-based models depicting three-dimensional elevation surface terrains. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"U\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">U<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Undershoot-150x100.png\" alt=\"Undershoot\" class=\"wp-image-4866\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Undershoot<\/strong>: <em>[editing]<\/em> An undershoot is considered to be a digitizing error in which the new line falls short of the intended connection segment. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-150x100.png\" alt=\"Union Tool\" class=\"wp-image-5468\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Union-Tool-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Union Tool<\/strong>: <em>[GIS processing]<\/em> The union tool spatially combines two data layers preserving the features and attributes from both layers at the same extents. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/08\/USGS-Earth-Explorer-Data-150x100.png\" alt=\"USGS Earth Explorer\" class=\"wp-image-4940\"\/><\/figure>\n<\/div>\n\n\n<p><strong>United States Geological Survey (USGS)<\/strong>: <em>[organization]<\/em> USGS is a United States agency responsible for Landsat satellites, nationwide map-making, and spatial data development. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/UTM_Zones-150x100.jpg\" alt=\"UTM Zones (False Northing, False Easting)\" class=\"wp-image-4596\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Universal Transverse Mercator (UTM)<\/strong>: <em>[coordinate system]<\/em> UTM coordinate system is a standard set of map projections with a central meridian for each six-degree wide UTM zone. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"V\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">V<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-150x100.png\" alt=\"Variable Buffer\" class=\"wp-image-5470\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Variable-Buffer.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Variable Distance Buffer<\/strong>: <em>[GIS processing]<\/em> Variable distance buffer uses a feature attribute from the input to create a ring around the feature that varies in distance. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-150x100.png\" alt=\"Vector Data Model\" class=\"wp-image-5473\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vector-Data-Model.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Vector Data Model<\/strong>: <em>[data structure]<\/em> A vector data model is a common GIS feature representation of spatial information based on defining coordinates and attribute information in points, polylines and polygons. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-150x100.png\" alt=\"Vertex\" class=\"wp-image-5474\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Vertex-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Vertex<\/strong>: <em>[data structure]<\/em> A vertex is a point that specifies a position on a line for arcs, polylines polygons. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"146\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Earth-Gravity-300x146.jpg\" alt=\"Earth Gravity\" class=\"wp-image-96261\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Earth-Gravity-300x146.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/11\/Earth-Gravity.jpg 678w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Vertical Datum<\/strong>: <em>[geodesy]<\/em> A vertical datum is a reference surface to which vertical heights are measured from the zero surfaces to which elevations or depths are referred. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-150x100.png\" alt=\"GPS VDOP\" class=\"wp-image-5478\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/GPS-VDOP.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Vertical Dilution of Precision (VDOP)<\/strong>: <em>[GPS]<\/em> VDOP is a quantitative measurement used to represent the quality of the height based on satellite geometry when taking GPS readings. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"W\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">W<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-150x100.png\" alt=\"Wavelength\" class=\"wp-image-5476\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wavelength.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Wavelength<\/strong>: <em>[remote sensing]<\/em> An electromagnetic wave produce sinusoidal patterns with the distance between the peak and trough of a wave for successive waves. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-medium is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"171\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/01\/Phone-Route-300x171.jpg\" alt=\"Phone Route\" class=\"wp-image-96138\" style=\"width:150px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/01\/Phone-Route-300x171.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/01\/Phone-Route-678x386.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/01\/Phone-Route-768x437.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/01\/Phone-Route.jpg 800w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Web Mapping Service (WMS)<\/strong>: <em>[Web Mapping]<\/em>  A WMS is pre-established tiles on the server side for viewing only that have features pre-cached at a set of scales. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/latitude-longitude-map-150x100.png\" alt=\"\" class=\"wp-image-4460\"\/><\/figure>\n<\/div>\n\n\n<p><strong>Web Feature Service (WFS)<\/strong>: <em>[Web Mapping]<\/em> A Web Feature Service allows you to visualize and edit features (points, lines, and polygons) over the internet. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-150x100.png\" alt=\"Wide Area Augmentation System\" class=\"wp-image-5480\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Wide-Area-Augmentation-System.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Wide Area Augmentation System (WAAS)<\/strong>: <em>[GPS]<\/em>  WAAS is a satellite-based signal correction that improves the estimation of GPS positions primarily by removing atmospheric distortion. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-150x100.png\" alt=\"Lines of Longitude\" class=\"wp-image-4734\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/05\/Longitude-538x360.png 538w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>World Geodetic System 1984<\/strong>: <em>[geodesy]<\/em> WGS84 is a reference ellipsoid used for defining spatial locations in three dimensions. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><a name=\"Z\"><\/a><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Z<\/h4>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-150x100.png\" alt=\"Zenith\" class=\"wp-image-5482\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1-233x155.png 233w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zenith-1.png 600w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>Zenith<\/strong>: <em>[mathematics]<\/em> Zenith is the angle measured directly in the z-direction (vertical direction opposite to the apparent gravitational force) on the imaginary celestial sphere at that location. <\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"100\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zonal-Operation-150x100.png\" alt=\"Zonal Operation\" class=\"wp-image-5483\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zonal-Operation-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/04\/Zonal-Operation-300x200.png 300w, 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