{"id":50083,"date":"2021-09-07T06:27:20","date_gmt":"2021-09-07T11:27:20","guid":{"rendered":"https:\/\/gisgeography.com\/?p=50083"},"modified":"2025-04-05T21:37:35","modified_gmt":"2025-04-06T02:37:35","slug":"spatial-analysis-periodic-table","status":"publish","type":"post","link":"https:\/\/gisgeography.com\/spatial-analysis-periodic-table\/","title":{"rendered":"The Periodic Table for Spatial Analysis"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2000\" height=\"1188\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table.jpg\" alt=\"Spatial Analysis Periodic Table\" class=\"wp-image-97510\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table.jpg 2000w, https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table-300x178.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table-678x403.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table-768x456.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2021\/09\/Spatial-Analysis-Periodic-Table-1536x912.jpg 1536w\" sizes=\"auto, (max-width: 2000px) 100vw, 2000px\" \/><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\">Introducing: The Periodic Table for Spatial Analysis<\/h2>\n\n\n\n<p>Each element in the <strong>Periodic Table for Spatial Analysis<\/strong> contains a set of spatial analysis tools. We&#8217;ve grouped common tools by color with vector analysis tools on the left and raster analysis on the right.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Vector Analysis\/Conversion<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"243\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-425x243.png\" alt=\"Spatial Join\" class=\"wp-image-19130\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-425x243.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-300x171.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-678x387.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-768x439.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-1536x878.png 1536w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-2048x1170.png 2048w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-50x29.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-174x98.png 174w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-70x40.png 70w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-200x114.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-550x314.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-115x66.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-1265x723.png 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/04\/Spatial-Join-850x486.png 850w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>1. Vector Conversion [VC]<\/strong> &#8211; Converts file formats for points, lines, and polygons and alters data models from vector to raster or vice versa. (Feature to raster, <a href=\"https:\/\/gisgeography.com\/rasterization-vectorization\/\">rasterization vs vectorization<\/a>)<br><strong>2. Extract [EX]<\/strong> &#8211; Creates a subset of features by clipping, selecting, and splitting vector features. (<a href=\"https:\/\/gisgeography.com\/clip-tool-gis\/\">Clip<\/a>, select, and split)<br><strong>3. Overlay [OV]<\/strong> &#8211; Overlays 2 or more vector layers and outputs layers based on overlapping features. (<a href=\"https:\/\/gisgeography.com\/intersect-tool-gis\/\">Intersect<\/a>, <a href=\"https:\/\/gisgeography.com\/union-tool\/\">union<\/a>, <a href=\"https:\/\/gisgeography.com\/erase-tool-gis\/\">erase tool<\/a>)<br><strong>4. Proximity [PX]<\/strong> &#8211; Generates output based on distances or proximity functions. (<a href=\"https:\/\/gisgeography.com\/buffer-tool-gis\/\">Buffer<\/a>, <a href=\"https:\/\/gisgeography.com\/voronoi-diagram-thiessen-polygons\/\">Voronoi diagrams<\/a>, and near functions)<br><strong>5. Spatial Join [SJ]<\/strong> &#8211; Joins attributes from a separate layer based on distance or spatial relationship. (1-M <a href=\"https:\/\/gisgeography.com\/spatial-join\/\">Spatial join<\/a> &#8220;Contains&#8221;, 1-1 Touches)<br><strong>6. Plot Diagrams [PD]<\/strong> &#8211; Builds a graph or diagram based on a set of attributes and geographical locations. (Scatter plot, histograms, bar plots)<br><strong>7. Geometry Shape [GS]<\/strong> &#8211; Computes the geometric shape of an object. (Compactness, perimeter\/area ratio, rectangular fit).<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Tables<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"222\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-425x222.png\" alt=\"Locations Map\" class=\"wp-image-20723\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-425x222.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-300x157.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-678x354.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-768x401.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-50x26.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-200x104.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-550x287.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-135x70.png 135w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-115x60.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-1265x660.png 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map-850x444.png 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/07\/What-is-GIS-Locations-Map.png 1391w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>8. Table Tools [TB]<\/strong> &#8211; Performs table functions for storing attribute data (Add field, create domains, <a href=\"https:\/\/gisgeography.com\/how-to-permanently-reorder-fields-in-arcgis\/\">reorder fields<\/a>)<br><strong>9. Add XY Coordinates [XY]<\/strong> &#8211; Converts a table of XY coordinates (latitude\/longitude) into a layer with a defined coordinate system. (<a href=\"https:\/\/gisgeography.com\/adding-excel-lat-long-coordinates-arcgis\/\">Add lat\/long coordinates<\/a>)<br><strong>10. Calculate Geometry [CG]<\/strong> &#8211; Computes the length of the geometric measurements in the attribute table of vector features. (Calculate length\/area)<br><strong>11. Join Table [JT]<\/strong> &#8211; Appends the attribute columns from one table into another table based on matching record keys. (1:1, 1:M, M:N)<br><strong>12. Relate [RL]<\/strong> &#8211; Generates a temporary table that displays matching records that associate with one or more matching records. (<a href=\"https:\/\/gisgeography.com\/relate-vs-join-attribute-tables-arcgis\/\">Relate vs Join<\/a>)<br><strong>13. Statistics [ST]<\/strong> &#8211; Calculates statistics based on a numerical field in a table. (<a href=\"https:\/\/gisgeography.com\/root-mean-square-error-rmse-gis\/\">RMSE<\/a>, <a href=\"https:\/\/gisgeography.com\/mean-absolute-error-mae-gis\/\">MAE<\/a>, sum, mean, count, standard deviation).<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_8c896d-9a{margin-top:25px;margin-bottom:25px;}.kb-row-layout-id50083_8c896d-9a > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_8c896d-9a > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_8c896d-9a > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:5px;padding-right:30px;padding-bottom:5px;padding-left:30px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_8c896d-9a{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}.kb-row-layout-id50083_8c896d-9a > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_8c896d-9a > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 1024px){.kb-row-layout-id50083_8c896d-9a{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}@media all and (max-width: 767px){.kb-row-layout-id50083_8c896d-9a > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_8c896d-9a{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_8c896d-9a alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_88baf1-28 > .kt-inside-inner-col,.kadence-column50083_88baf1-28 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_88baf1-28 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_88baf1-28 > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_88baf1-28 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_88baf1-28 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_88baf1-28{position:relative;}@media all and (max-width: 1024px){.kadence-column50083_88baf1-28 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_88baf1-28 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_88baf1-28 inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57, .wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57[data-kb-block=\"kb-adv-heading50083_29139b-57\"]{padding-top:10px;padding-bottom:15px;font-size:20px;font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57[data-kb-block=\"kb-adv-heading50083_29139b-57\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading50083_29139b-57[data-kb-block=\"kb-adv-heading50083_29139b-57\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<div class=\"kt-adv-heading50083_29139b-57 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading50083_29139b-57\"><strong>Enhance your GIS skills:<\/strong><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_a5da35-4f{margin-top:0px;margin-bottom:0px;}.kb-row-layout-id50083_a5da35-4f > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_a5da35-4f > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_a5da35-4f > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:0px;padding-bottom:0px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_a5da35-4f > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_a5da35-4f > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 767px){.kb-row-layout-id50083_a5da35-4f > .kt-row-column-wrap{padding-bottom:5px;grid-template-columns:minmax(0, 1fr);}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_a5da35-4f alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_d60cbe-8b > .kt-inside-inner-col{padding-top:0px;padding-bottom:0px;}.kadence-column50083_d60cbe-8b > .kt-inside-inner-col,.kadence-column50083_d60cbe-8b > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_d60cbe-8b > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_d60cbe-8b > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_d60cbe-8b > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_d60cbe-8b > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_d60cbe-8b{position:relative;}.kadence-column50083_d60cbe-8b, .kt-inside-inner-col > .kadence-column50083_d60cbe-8b:not(.specificity){margin-top:0px;margin-bottom:0px;}@media all and (max-width: 1024px){.kadence-column50083_d60cbe-8b > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_d60cbe-8b > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_d60cbe-8b inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.kt-post-loop50083_0f3e09-e1 .kadence-post-image{padding-top:0px;padding-right:15px;padding-bottom:10px;padding-left:0px;}.kt-post-loop50083_0f3e09-e1 .kt-feat-image-align-left{grid-template-columns:30% auto;}.kt-post-loop50083_0f3e09-e1 .kt-post-grid-wrap{gap:5px 25px;}.kt-post-loop50083_0f3e09-e1 .kt-blocks-post-grid-item{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;overflow:hidden;}.kt-post-loop50083_0f3e09-e1 .kt-blocks-post-grid-item header{padding-top:0px;padding-right:0px;padding-bottom:10px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;}.kt-post-loop50083_0f3e09-e1 .kt-blocks-post-grid-item .kt-blocks-above-categories{font-size:13px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_0f3e09-e1 .kt-blocks-post-grid-item .entry-title{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:18px;line-height:20px;}.kt-post-loop50083_0f3e09-e1 .entry-content{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;line-height:24px;}.kt-post-loop50083_0f3e09-e1 .kt-blocks-post-footer{border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:12px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_0f3e09-e1 .entry-content:after{height:0px;}.kt-post-loop50083_0f3e09-e1 .kb-filter-item{border-top-width:0px;border-right-width:0px;border-bottom-width:2px;border-left-width:0px;padding-top:5px;padding-right:8px;padding-bottom:5px;padding-left:8px;margin-top:0px;margin-right:10px;margin-bottom:0px;margin-left:0px;}<\/style><div class=\"wp-block-kadence-postgrid kt-blocks-post-loop-block alignnone kt-post-loop50083_0f3e09-e1 kt-post-grid-layout-grid \"><div class=\"kt-post-grid-layout-grid-wrap kt-post-grid-wrap\" data-columns-xxl=\"2\" data-columns-xl=\"2\" data-columns-md=\"2\" data-columns-sm=\"2\" data-columns-xs=\"1\" data-columns-ss=\"1\"data-item-selector=\".kt-post-masonry-item\" aria-label=\"Post Carousel\"><article class=\"kt-blocks-post-grid-item post-19227 post type-post status-publish format-standard has-post-thumbnail hentry category-gis-analysis tag-what-is-gis\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:53%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/spatial-analysis\/\" aria-label=\"The Power of Spatial Analysis: Patterns in Geography\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"106\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-200x106.jpg\" class=\"attachment-Small Size size-Small Size wp-post-image\" alt=\"Geospatial Analysis\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-200x106.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-300x159.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-678x360.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-768x408.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-425x226.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-550x292.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-115x61.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-1000x531.jpg 1000w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1-360x191.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/09\/Geospatial-Analysis-1.jpg 1272w\" sizes=\"auto, (max-width: 200px) 100vw, 200px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/spatial-analysis\/\">The Power of Spatial Analysis: Patterns in Geography<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><article class=\"kt-blocks-post-grid-item post-5189 post type-post status-publish format-standard has-post-thumbnail hentry category-data-sources tag-gis-formats\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:68%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/gis-formats\/\" aria-label=\"The Ultimate List of GIS Formats and Geospatial File Extensions\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"136\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-200x136.png\" class=\"attachment-Small Size size-Small Size wp-post-image\" alt=\"GIS Formats\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-200x136.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-300x204.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-678x461.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-768x522.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-50x34.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-425x289.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-550x374.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-115x78.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner-228x155.png 228w, https:\/\/gisgeography.com\/wp-content\/uploads\/2015\/09\/GIS-Formats-Banner.png 800w\" sizes=\"auto, (max-width: 200px) 100vw, 200px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/gis-formats\/\">The Ultimate List of GIS Formats and Geospatial File Extensions<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><\/div><\/div><!-- .wp-block-kadence-postgrid --><\/div><\/div>\n\n<\/div><\/div><\/div><\/div>\n\n<\/div><\/div>\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Editing\/Cartography<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"283\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-425x283.png\" alt=\"Editing Generalize\" class=\"wp-image-20386\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-425x283.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-300x200.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-50x33.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-150x100.png 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-200x133.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-550x367.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize-115x77.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Editing-Generalize.png 600w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>14. Editing [ED]<\/strong> &#8211; Performs an editing function using the vertices and geometry in one or more layers. (<a href=\"https:\/\/gisgeography.com\/gis-editing-tools\/\">Editing tools<\/a>, densify, trim, snap, and extend)<br><strong>15. Conflation [CF]<\/strong> &#8211; Resolves conflicts between two layers that display the same features with mismatching geometries. (Edge-matching, rubber sheeting, <a href=\"https:\/\/gisgeography.com\/conflation-edgematching-rubbersheeting\/\">conflation<\/a>)<br><strong>16. Grid Index [GI]<\/strong> &#8211; Produces a set of consecutive rectangular map sheets that follow a linear feature for mapbook production. (Strip Map, fishnet, tessellation, <a href=\"https:\/\/gisgeography.com\/how-to-create-qgis-atlas-mapbooks\/\">QGIS Atlas<\/a>, <a href=\"https:\/\/gisgeography.com\/data-driven-pages-mapbooks-arcgis\/\">data driven pages<\/a>)<br><strong>17. Cartographic [CA]<\/strong> &#8211; Enhances or generalizes features in a dataset for cartographic display and aesthetic quality. (Smooth, simplify, aggregate).<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">3D Analysis<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"678\" height=\"391\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Intersect-3D-678x391.jpg\" alt=\"Intersect 3D\" class=\"wp-image-97454\" style=\"width:400px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Intersect-3D-678x391.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Intersect-3D-300x173.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Intersect-3D-768x443.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Intersect-3D.jpg 1000w\" sizes=\"auto, (max-width: 678px) 100vw, 678px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>18. 3D Analysis [3D]<\/strong> &#8211; Performs an overlay or proximity analysis with 3D features. (<a href=\"https:\/\/gisgeography.com\/3d-analysis\/\">3D analysis<\/a> buffer, intersect, or union)<br><strong>19. Line of Sight Visibility [LS]<\/strong> &#8211; Identifies obstruction and non-obstruction sections of a straight line from an observer. (<a href=\"https:\/\/gisgeography.com\/line-of-sight-viewshed-visibility-analysis\/\">Line of sight<\/a>)<br><strong>20. Volume [VS]<\/strong> &#8211; Calculates the amount of space above, below, within, or for the purpose of removing or adding material. (Cut\/fill)<br><strong>21. Viewshed [VW]<\/strong> &#8211; Determines locations visible to an observer in all directions with the output as a visibility raster.<br><strong>22. Skyline [SL]<\/strong> &#8211; Displays visible and obstructed shadowed areas similar to a 3D fan pointing from an observer&#8217;s point of view.<br><strong>23. Space-time Cubes [SC]<\/strong> &#8211; Builds temporal and 3D cubes representing slices of time in a geographic area. (<a href=\"https:\/\/gisgeography.com\/space-time-cubes\/\">Space-time cubes<\/a>)<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"20 GIS Tools Every Geospatial Analyst Should Know\" width=\"720\" height=\"405\" src=\"https:\/\/www.youtube.com\/embed\/TZQ0icETZ6E?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Network Analysis<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"776\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Shortest-Route-Network-Analysis.jpg\" alt=\"Shortest Route Network Analysis\" class=\"wp-image-97431\" style=\"width:400px\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Shortest-Route-Network-Analysis.jpg 1000w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Shortest-Route-Network-Analysis-300x233.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Shortest-Route-Network-Analysis-678x526.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Shortest-Route-Network-Analysis-768x596.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>24. Route [RT]<\/strong> &#8211; Finds the optimal route using a set of points and a network dataset. (<a href=\"https:\/\/gisgeography.com\/network-analysis\/\">Network analysis<\/a> fastest route, find nearest, or shortest distance)<br><strong>25. Directions [DR]<\/strong> &#8211; Lists the turns, streets, and directions from an origin to a destination point using a network dataset.<br><strong>26. Optimal Site [OS]<\/strong> &#8211; Selects optimal sites from existing facilities, competing stores, and available demand. (<a href=\"https:\/\/gisgeography.com\/optimal-business-location-allocation\/\">Location-allocation<\/a>)<br><strong>27. Coverage [CV]<\/strong> &#8211; Computes the coverage or accessibility that a facility can be reached for a given distance, time, and network dataset. (Service area)<br><strong>28. OD Cost Matrix [CM]<\/strong> &#8211; Measures the least cost path from multiple origin points to multiple destination points.<br><strong>29. Huff Model [HM]<\/strong> &#8211; Predicts the probability that consumers will patron retail stores using store size, distance, and census tract population. (<a href=\"https:\/\/gisgeography.com\/huff-gravity-model\/\">Huff gravity model<\/a>)<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Data Management<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"164\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-425x164.png\" alt=\"Merge Tool\" class=\"wp-image-44697\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-425x164.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-300x116.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-678x261.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-768x296.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-50x19.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-200x77.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-550x212.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-115x44.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-1265x488.png 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool-360x139.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/02\/Merge-Tool.png 1453w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"270\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-425x270.png\" alt=\"Geoenrichment\" class=\"wp-image-45541\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-425x270.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-300x191.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-678x431.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-768x489.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-50x32.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-200x127.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-550x350.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-115x73.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment-360x229.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Geoenrichment.png 1100w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>30. Data Management [DM]<\/strong> &#8211; Manages layers with a set of tools to develop, alter, and maintain layers (<a href=\"https:\/\/gisgeography.com\/merge-tool-gis\/\">Merge<\/a>, <a href=\"https:\/\/gisgeography.com\/append-tool-gis\/\">append<\/a>, data compare)<br><strong>31. Projections [PJ]<\/strong> &#8211; Assigns a coordinate reference system for a layer. (<a href=\"https:\/\/gisgeography.com\/arcgis-projections-define-project\/\">Project<\/a>, define projection)<br><strong>32. Generalize Vector [GV]<\/strong> &#8211; Combines adjacent features or slivers based on common attribute values or shared borders. (<a href=\"https:\/\/gisgeography.com\/dissolve-tool-gis\/\">Dissolve<\/a> and eliminate)<br><strong>33. Address Geocoding (AD)<\/strong> &#8211; Translates addresses into geographic locations with latitude and longitude coordinates. (<a href=\"https:\/\/gisgeography.com\/geocoding\/\">Geocode<\/a>, reverse geocode)<br><strong>34. Topology [TP]<\/strong> &#8211; Fixes and catches editing errors such as overshoots, undershoots, slivers, overlaps, and gaps. (<a href=\"https:\/\/gisgeography.com\/topology-rules-arcgis\/\">Topology rules<\/a>)<br><strong>35. Linear Referencing [LR]<\/strong> &#8211; Stores relative positions on a line feature represented by m-values for point\/line events. (<a href=\"https:\/\/gisgeography.com\/linear-referencing-systems\/\">Linear referencing systems<\/a>)<br><strong>36. Spatial Adjustment [SA]<\/strong> &#8211; Aligns and transforms a vector layer that has been displaced, rotated, or distorted like georeferencing for vectors. (Vector bender, displacement links)<br><strong>37. GeoEnrich [GE]<\/strong> &#8211; Ameliorates existing data with value-added information such as demographic, education, or income attributes. (<a href=\"https:\/\/gisgeography.com\/geoenrichment\/\">GeoEnrichment<\/a>)<br><strong>38. Sampling [SP]<\/strong> &#8211; Creates a subset of data for sampling at set intervals or randomly. (Regular points, random points in extent)<br><strong>39. Geotagging [GT]<\/strong> &#8211; Assigns geographic coordinates to digital photos through GPS without georeferencing. (<a href=\"https:\/\/gisgeography.com\/geotagging\/\">Geotagging<\/a>)<br><strong>40. Parcel Fabric [PF]<\/strong> &#8211; Constructs cadastral specific to managing parcel fabric. (Cadastral divisions, split polygon)<br><strong>41. Attachments [AT]<\/strong> &#8211; Builds attachments to store photos internally as a table relationship.<br><strong>42. Full Motion Video [FMV]<\/strong> &#8211; Geo-enables video with the footprints coordinated on a map. (<a href=\"https:\/\/gisgeography.com\/full-motion-video-fmv\/\">Full motion video<\/a>)<br><strong>43. COGO [CO]<\/strong> &#8211; Captures coordinates, bearings, and distances from transverse land survey measurements. (<a href=\"https:\/\/gisgeography.com\/cogo-coordinate-geometry\/\">COGO &#8211; Coordinate Geometry<\/a>)<br><strong>44. Point Cloud [PC]<\/strong> &#8211; Manages LAS files with a set of tools to maintain, alter, and interpolate point clouds.<br><strong>45. Web Service [WS]<\/strong> &#8211; Deploys or imports features from a layer as a web feature\/mapping service. (Web feature service, GeoRSS)<br><strong>46. TIN [TIN]<\/strong> &#8211; Creates a triangular irregular network for depicting three-dimensional terrain surfaces. (<a href=\"https:\/\/gisgeography.com\/triangular-irregular-network-tin\/\">TIN mesh creation<\/a>)<br><strong>47. Indoor Mapping [IM]<\/strong> &#8211; Incorporates indoor floor plans with digital formats like BIM, Revit, and CAD. (<a href=\"https:\/\/gisgeography.com\/indoor-mapping\/\">Indoor mapping<\/a>)<br><strong>48. Temporal [TM]<\/strong> &#8211; Adds time properties to layers with the date and\/or time (Convert time zone, update time field, <a href=\"https:\/\/gisgeography.com\/time-series-animation-arcgis\/\">temporal animation<\/a>)<br><strong>49. Real-time Tracking [TR]<\/strong> &#8211; Streams real-time movement of objects or change in status over time. (GeoEvent server, <a href=\"https:\/\/gisgeography.com\/geofence-geofencing\/\">geofencing<\/a>, make tracking layer)<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Emerging Technology<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-medium\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"223\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-300x223.png\" alt=\"Artificial Intelligence\" class=\"wp-image-66555\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-300x223.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-50x37.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-200x148.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-425x315.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-550x408.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-115x85.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence-360x267.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/Artificial-Intelligence.png 582w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>50. Big Data [BD]<\/strong> &#8211; Analyzes and extracts data from datasets too large and complex with geographic locations. (GeoAnalytics Desktop Tools)<br><strong>51. Machine Learning [ML]<\/strong> &#8211; Uses neural networks for classification, prediction, and segmentation through training and labeling. (Deep learning toolset, <a href=\"https:\/\/gisgeography.com\/deep-machine-learning-ml-artificial-intelligence-ai-gis\/\">machine learning<\/a>)<br><strong>52. Data Engineering [DE]<\/strong> &#8211; Validates, cleans, and maintains spatial data into a usable form for analysis.<br><strong>53. IoT [IOT]<\/strong> &#8211; Analyzes real-time data feeds and sensors from the Internet of Things (IoT) platform. (<a href=\"https:\/\/gisgeography.com\/arcgis-velocity\/\">ArcGIS Velocity<\/a>)<br><strong>54. Agent-based Simulation and Modeling [AS]<\/strong> &#8211; Simulate scenarios and the emergence of phenomena through individual interactions in geographic space. (Multi-agent modeling environment)<br><strong>55. Virtual Reality [VR]<\/strong> &#8211; Replaces the field of vision through headsets in a spatial environment.<br><strong>56. Augmented Reality [AR]<\/strong> &#8211; Enhances 3D features on your phone\u2019s display to interact spatially with the outside world. (<a href=\"https:\/\/gisgeography.com\/augmented-reality-applications-gis\/\">Augmented reality<\/a>)<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_5d2795-8d{margin-top:25px;margin-bottom:25px;}.kb-row-layout-id50083_5d2795-8d > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_5d2795-8d > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_5d2795-8d > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:5px;padding-right:30px;padding-bottom:5px;padding-left:30px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_5d2795-8d{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}.kb-row-layout-id50083_5d2795-8d > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_5d2795-8d > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 1024px){.kb-row-layout-id50083_5d2795-8d{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}@media all and (max-width: 767px){.kb-row-layout-id50083_5d2795-8d > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_5d2795-8d{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_5d2795-8d alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_7918fc-b5 > .kt-inside-inner-col,.kadence-column50083_7918fc-b5 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_7918fc-b5 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_7918fc-b5 > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_7918fc-b5 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_7918fc-b5 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_7918fc-b5{position:relative;}@media all and (max-width: 1024px){.kadence-column50083_7918fc-b5 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_7918fc-b5 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_7918fc-b5 inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd, .wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd[data-kb-block=\"kb-adv-heading50083_178a0b-dd\"]{padding-top:10px;padding-bottom:15px;font-size:20px;font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd[data-kb-block=\"kb-adv-heading50083_178a0b-dd\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading50083_178a0b-dd[data-kb-block=\"kb-adv-heading50083_178a0b-dd\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<div class=\"kt-adv-heading50083_178a0b-dd wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading50083_178a0b-dd\"><strong>Learn about these emerging technologies:<\/strong><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_a0f5be-a5{margin-top:0px;margin-bottom:0px;}.kb-row-layout-id50083_a0f5be-a5 > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_a0f5be-a5 > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_a0f5be-a5 > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:0px;padding-bottom:0px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_a0f5be-a5 > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_a0f5be-a5 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 767px){.kb-row-layout-id50083_a0f5be-a5 > .kt-row-column-wrap{padding-bottom:5px;grid-template-columns:minmax(0, 1fr);}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_a0f5be-a5 alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_3adcb8-4b > .kt-inside-inner-col{padding-top:0px;padding-bottom:0px;}.kadence-column50083_3adcb8-4b > .kt-inside-inner-col,.kadence-column50083_3adcb8-4b > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_3adcb8-4b > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_3adcb8-4b > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_3adcb8-4b > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_3adcb8-4b > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_3adcb8-4b{position:relative;}.kadence-column50083_3adcb8-4b, .kt-inside-inner-col > .kadence-column50083_3adcb8-4b:not(.specificity){margin-top:0px;margin-bottom:0px;}@media all and (max-width: 1024px){.kadence-column50083_3adcb8-4b > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_3adcb8-4b > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_3adcb8-4b inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.kt-post-loop50083_9f3494-6f .kadence-post-image{padding-top:0px;padding-right:15px;padding-bottom:10px;padding-left:0px;}.kt-post-loop50083_9f3494-6f .kt-feat-image-align-left{grid-template-columns:30% auto;}.kt-post-loop50083_9f3494-6f .kt-post-grid-wrap{gap:5px 25px;}.kt-post-loop50083_9f3494-6f .kt-blocks-post-grid-item{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;overflow:hidden;}.kt-post-loop50083_9f3494-6f .kt-blocks-post-grid-item header{padding-top:0px;padding-right:0px;padding-bottom:10px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;}.kt-post-loop50083_9f3494-6f .kt-blocks-post-grid-item .kt-blocks-above-categories{font-size:13px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_9f3494-6f .kt-blocks-post-grid-item .entry-title{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:18px;line-height:20px;}.kt-post-loop50083_9f3494-6f .entry-content{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;line-height:24px;}.kt-post-loop50083_9f3494-6f .kt-blocks-post-footer{border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:12px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_9f3494-6f .entry-content:after{height:0px;}.kt-post-loop50083_9f3494-6f .kb-filter-item{border-top-width:0px;border-right-width:0px;border-bottom-width:2px;border-left-width:0px;padding-top:5px;padding-right:8px;padding-bottom:5px;padding-left:8px;margin-top:0px;margin-right:10px;margin-bottom:0px;margin-left:0px;}<\/style><div class=\"wp-block-kadence-postgrid kt-blocks-post-loop-block alignnone kt-post-loop50083_9f3494-6f kt-post-grid-layout-grid \"><div class=\"kt-post-grid-layout-grid-wrap kt-post-grid-wrap\" data-columns-xxl=\"2\" data-columns-xl=\"2\" data-columns-md=\"2\" data-columns-sm=\"2\" data-columns-xs=\"1\" data-columns-ss=\"1\"data-item-selector=\".kt-post-masonry-item\" aria-label=\"Post Carousel\"><article class=\"kt-blocks-post-grid-item post-66587 post type-post status-publish format-standard has-post-thumbnail hentry category-gis-analysis tag-data-science\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:56.5%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/geoanalytics\/\" aria-label=\"Geoanalytics 101: Exploring Spatial Data Science\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"113\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-200x113.png\" class=\"attachment-Small Size size-Small Size wp-post-image\" alt=\"GeoAnalytics\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-200x113.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-300x170.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-678x384.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-768x435.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-50x28.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-580x326.png 580w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-425x241.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-550x312.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-115x65.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-1265x717.png 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics-360x204.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2022\/03\/GeoAnalytics.png 1500w\" sizes=\"auto, (max-width: 200px) 100vw, 200px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/geoanalytics\/\">Geoanalytics 101: Exploring Spatial Data Science<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><article class=\"kt-blocks-post-grid-item post-17580 post type-post status-publish format-standard has-post-thumbnail hentry category-gis-analysis tag-data-science\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:50%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/deep-machine-learning-ml-artificial-intelligence-ai-gis\/\" aria-label=\"The Rise of Machine Learning and AI in GIS\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"100\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-200x100.png\" class=\"attachment-Small Size size-Small Size wp-post-image\" alt=\"Machine Learning ML Artificial Intelligence AI in GIS\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-200x100.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-300x150.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-678x340.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-768x385.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-50x25.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-425x213.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-550x276.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS-115x58.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2018\/01\/Machine-Learning-Artificial-Intelligence-GIS.png 778w\" sizes=\"auto, (max-width: 200px) 100vw, 200px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/deep-machine-learning-ml-artificial-intelligence-ai-gis\/\">The Rise of Machine Learning and AI in GIS<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><\/div><\/div><!-- .wp-block-kadence-postgrid --><\/div><\/div>\n\n<\/div><\/div><\/div><\/div>\n\n<\/div><\/div>\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Raster Data Management<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"150\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-425x150.jpg\" alt=\"Mosaic Raster Tool\" class=\"wp-image-44804\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-425x150.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-300x106.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-678x239.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-768x271.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-1536x541.jpg 1536w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-50x18.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-900x320.jpg 900w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-200x70.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-550x194.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-115x41.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-1265x446.jpg 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-360x127.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool-1550x546.jpg 1550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Mosaic-Raster-Tool.jpg 1705w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>57. Georeferencing [GR]<\/strong> &#8211; Stretches, scales, rotates, and skews raster images to better relate to geographic space. (<a href=\"https:\/\/gisgeography.com\/georeferencing\/\">Georeferencing<\/a>)<br><strong>58. Mosaic [MO]<\/strong> &#8211; Combines multiple raster images into a seamless, composite raster image. (<a href=\"https:\/\/gisgeography.com\/mosaic-raster\/\">Mosaic<\/a>)<br><strong>59. Raster Creation [RC]<\/strong> &#8211; Generates a raster for a given extent at a specific cell size. (Create a random raster, create a constant raster)<br><strong>60. Spatial Autocorrelation [AL]<\/strong> &#8211; Measures how dispersed or clustered cells are located in a raster. (<a href=\"https:\/\/gisgeography.com\/spatial-autocorrelation-moran-i-gis\/\">Moran&#8217;s I<\/a>)<br><strong>61. Generalization [RG]<\/strong> &#8211; Cleans raster data by generalizing, smoothing, and altering cells. (Nibble, shrink, expand)<br><strong>62. Multidimensional [MD]<\/strong> &#8211; Provides an interface for array-oriented data for storing multidimensional variables. (NetCDF)<br><strong>63. Resample [RS]<\/strong> &#8211; Updates the cell size for converting raster images. (<a href=\"https:\/\/gisgeography.com\/raster-resampling\/\">Raster resample<\/a>: Nearest neighbor, bilinear, and cubic convolution)<br><strong>64. Raster Painting [PA]<\/strong> &#8211; Draws and erases raster cells with a set of brush, fill, and erase tools.<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Raster Analysis<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"147\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-425x147.jpg\" alt=\"Least Cost Path Analysis\" class=\"wp-image-44853\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-425x147.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-300x104.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-678x235.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-768x266.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-50x17.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-200x69.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-550x191.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-115x40.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-1265x439.jpg 1265w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis-360x125.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/10\/Least-Cost-Path-Analysis.jpg 1344w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>65. Raster Analysis [RA]<\/strong> &#8211; Performs <a href=\"https:\/\/gisgeography.com\/raster-analysis\/\">raster analysis functions<\/a> for a raster grid dataset. (Analyze patterns)<br><strong>66. Map Algebra [MA]<\/strong> &#8211; Applies math-like operations in local, zonal, focal, and global configurations. (<a href=\"https:\/\/gisgeography.com\/map-algebra-global-zonal-focal-local\/\">Map algebra<\/a>)<br><strong>67. Contours [CN]<\/strong> &#8211; Produces lines of constant elevation to represent the topography of the landscape. (<a href=\"https:\/\/gisgeography.com\/contour-lines-topographic-map\/\">Contours<\/a>)<br><strong>68. Zonal Statistics [ZS]<\/strong> &#8211; Generates statistics for defined zones of a raster surface. (<a href=\"https:\/\/gisgeography.com\/zonal-statistics\/\">Zonal statistics<\/a> &#8211; mean, sum, and majority)<br><strong>69. Cost Path [CP]<\/strong> &#8211; Finds the most cost-effective path, from a start point to a destination, which accumulates the least amount of cost. (<a href=\"https:\/\/gisgeography.com\/least-cost-path-analysis\/\">Least cost path<\/a>)<br><strong>70. Raster Processing [RP]<\/strong> &#8211; Creates a subset of features by clipping, selecting, and splitting raster grids. (<a href=\"https:\/\/gisgeography.com\/clip-rasters-arcgis-polygon-boundary\/\">Raster clip<\/a>, split raster)<br><strong>71. Spatial Regression [RE]<\/strong> &#8211; Generates a prediction surface based on explanatory variables. (Ordinary least squares regression, <a href=\"https:\/\/gisgeography.com\/geographically-weighted-regression\/\">spatial regression<\/a>)<br><strong>72. Terrain Analysis [TA]<\/strong> &#8211; Calculates the characteristics of the terrain from an input raster. (<a href=\"https:\/\/gisgeography.com\/flow-direction\/\">Slope<\/a>, morphometry, TPI, and roughness)<br><strong>73. Math Function [MF]<\/strong> &#8211; Executes a math function to update the numerical value on a cell-by-cell basis. (Arithmetic, power, exponential, and logarithmic)<br><strong>74. Suitability [SU]<\/strong> &#8211; Overlays raster surfaces based on criteria to analyze suitability. (Fuzzy logic weighted sum)<br><strong>75. Conditional [CON]<\/strong> &#8211; Performs a conditional statement on a raster that generates a binary output. (Greater than, equal to)<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_b8972c-44{margin-top:25px;margin-bottom:25px;}.kb-row-layout-id50083_b8972c-44 > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_b8972c-44 > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_b8972c-44 > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:5px;padding-right:30px;padding-bottom:5px;padding-left:30px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_b8972c-44{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}.kb-row-layout-id50083_b8972c-44 > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_b8972c-44 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 1024px){.kb-row-layout-id50083_b8972c-44{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}@media all and (max-width: 767px){.kb-row-layout-id50083_b8972c-44 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_b8972c-44{border-top:1px solid #dedede;border-right:1px solid #dedede;border-bottom:1px solid #dedede;border-left:1px solid #dedede;}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_b8972c-44 alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col,.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_e32b3a-c2{position:relative;}@media all and (max-width: 1024px){.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_e32b3a-c2 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_e32b3a-c2 inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93, .wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93[data-kb-block=\"kb-adv-heading50083_7e766f-93\"]{padding-top:10px;padding-bottom:15px;font-size:20px;font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93[data-kb-block=\"kb-adv-heading50083_7e766f-93\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading50083_7e766f-93[data-kb-block=\"kb-adv-heading50083_7e766f-93\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<div class=\"kt-adv-heading50083_7e766f-93 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading50083_7e766f-93\"><strong>Explore raster data and imagery:<\/strong><\/div>\n\n\n<style>.kb-row-layout-wrap.wp-block-kadence-rowlayout.kb-row-layout-id50083_bf5318-b2{margin-top:0px;margin-bottom:0px;}.kb-row-layout-id50083_bf5318-b2 > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id50083_bf5318-b2 > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id50083_bf5318-b2 > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-sm, 1rem);padding-top:0px;padding-bottom:0px;grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id50083_bf5318-b2 > .kt-row-layout-overlay{opacity:0.30;}@media all and (max-width: 1024px){.kb-row-layout-id50083_bf5318-b2 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 767px){.kb-row-layout-id50083_bf5318-b2 > .kt-row-column-wrap{padding-bottom:5px;grid-template-columns:minmax(0, 1fr);}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id50083_bf5318-b2 alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column50083_cfdd34-30 > .kt-inside-inner-col{padding-top:0px;padding-bottom:0px;}.kadence-column50083_cfdd34-30 > .kt-inside-inner-col,.kadence-column50083_cfdd34-30 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column50083_cfdd34-30 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column50083_cfdd34-30 > .kt-inside-inner-col{flex-direction:column;}.kadence-column50083_cfdd34-30 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column50083_cfdd34-30 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column50083_cfdd34-30{position:relative;}.kadence-column50083_cfdd34-30, .kt-inside-inner-col > .kadence-column50083_cfdd34-30:not(.specificity){margin-top:0px;margin-bottom:0px;}@media all and (max-width: 1024px){.kadence-column50083_cfdd34-30 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column50083_cfdd34-30 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column50083_cfdd34-30 inner-column-1\"><div class=\"kt-inside-inner-col\"><style>.kt-post-loop50083_2eac1f-8d .kadence-post-image{padding-top:0px;padding-right:15px;padding-bottom:10px;padding-left:0px;}.kt-post-loop50083_2eac1f-8d .kt-feat-image-align-left{grid-template-columns:30% auto;}.kt-post-loop50083_2eac1f-8d .kt-post-grid-wrap{gap:5px 25px;}.kt-post-loop50083_2eac1f-8d .kt-blocks-post-grid-item{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;overflow:hidden;}.kt-post-loop50083_2eac1f-8d .kt-blocks-post-grid-item header{padding-top:0px;padding-right:0px;padding-bottom:10px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;}.kt-post-loop50083_2eac1f-8d .kt-blocks-post-grid-item .kt-blocks-above-categories{font-size:13px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_2eac1f-8d .kt-blocks-post-grid-item .entry-title{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:18px;line-height:20px;}.kt-post-loop50083_2eac1f-8d .entry-content{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;line-height:24px;}.kt-post-loop50083_2eac1f-8d .kt-blocks-post-footer{border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:12px;line-height:20px;text-transform:uppercase;}.kt-post-loop50083_2eac1f-8d .entry-content:after{height:0px;}.kt-post-loop50083_2eac1f-8d .kb-filter-item{border-top-width:0px;border-right-width:0px;border-bottom-width:2px;border-left-width:0px;padding-top:5px;padding-right:8px;padding-bottom:5px;padding-left:8px;margin-top:0px;margin-right:10px;margin-bottom:0px;margin-left:0px;}<\/style><div class=\"wp-block-kadence-postgrid kt-blocks-post-loop-block alignnone kt-post-loop50083_2eac1f-8d kt-post-grid-layout-grid \"><div class=\"kt-post-grid-layout-grid-wrap kt-post-grid-wrap\" data-columns-xxl=\"2\" data-columns-xl=\"2\" data-columns-md=\"2\" data-columns-sm=\"2\" data-columns-xs=\"1\" data-columns-ss=\"1\"data-item-selector=\".kt-post-masonry-item\" aria-label=\"Post Carousel\"><article class=\"kt-blocks-post-grid-item post-9162 post type-post status-publish format-standard has-post-thumbnail hentry category-data-sources tag-orthoimagery\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:56.333333333333%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/free-satellite-imagery-data-list\/\" aria-label=\"15 Free Satellite Imagery Data Sources\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"169\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/01\/Free-Satellite-Imagery-300x169.jpg\" class=\"attachment-medium size-medium wp-post-image\" alt=\"Free Satellite Imagery\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/01\/Free-Satellite-Imagery-300x169.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/01\/Free-Satellite-Imagery-678x382.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/01\/Free-Satellite-Imagery-768x432.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/01\/Free-Satellite-Imagery.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/free-satellite-imagery-data-list\/\">15 Free Satellite Imagery Data Sources<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><article class=\"kt-blocks-post-grid-item post-77327 post type-post status-publish format-standard has-post-thumbnail hentry category-gis-analysis tag-raster-tools\"><div class=\"kt-blocks-post-grid-item-inner-wrap kt-feat-image-align-left kt-feat-image-mobile-align-side\"><div class=\"kadence-post-image\"><div class=\"kadence-post-image-intrisic kt-image-ratio-nocrop\" style=\"padding-bottom:56.333333333333%;\"><div class=\"kadence-post-image-inner-intrisic\"><a aria-hidden=\"true\" tabindex=\"-1\" role=\"presentation\" href=\"https:\/\/gisgeography.com\/raster-analysis\/\" aria-label=\"Raster Analysis in GIS &#8211; Tools and Techniques\" class=\"kadence-post-image-inner-wrap\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"169\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-300x169.jpg\" class=\"attachment-medium size-medium wp-post-image\" alt=\"Raster Analysis Feature\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-300x169.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-678x381.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-768x432.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-200x113.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-425x239.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-550x309.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-115x65.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-1000x563.jpg 1000w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature-360x203.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2023\/01\/Raster-Analysis-Feature.jpg 1200w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/div><\/div><\/div><div class=\"kt-blocks-post-grid-item-inner\"><header><h6 class=\"entry-title\"><a href=\"https:\/\/gisgeography.com\/raster-analysis\/\">Raster Analysis in GIS &#8211; Tools and Techniques<\/a><\/h6><div class=\"kt-blocks-post-top-meta\"><\/div><\/header><div class=\"entry-content\"><\/div><footer class=\"kt-blocks-post-footer\"><div class=\"kt-blocks-post-footer-left\"><\/div><div class=\"kt-blocks-post-footer-right\"><\/div><\/footer><\/div><\/div><\/article><\/div><\/div><!-- .wp-block-kadence-postgrid --><\/div><\/div>\n\n<\/div><\/div><\/div><\/div>\n\n<\/div><\/div>\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"252\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-425x252.jpg\" alt=\"Photogrammetry Point Cloud\" class=\"wp-image-20503\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-425x252.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-300x178.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-678x402.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-768x455.jpg 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-50x30.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-200x118.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-550x326.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-115x68.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud-850x503.jpg 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2019\/12\/Photogrammetry-Point-Cloud.jpg 1025w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>76. Band Index [BA]<\/strong> &#8211; Converts a set of imagery bands by leveraging the inherent wavelength properties. (<a href=\"https:\/\/gisgeography.com\/ndvi-normalized-difference-vegetation-index\/\">NDVI<\/a>, tasseled cap, wetness index)<br><strong>77. Image Stretching [IS]<\/strong> &#8211; Arranges the display of an image by adjusting brightness, contrast, and gamma properties.<br><strong>78. Image Classification [IC]<\/strong> &#8211; Assigns land cover classes to imagery pixels based on their spectral properties. (<a href=\"https:\/\/gisgeography.com\/supervised-unsupervised-classification-arcgis\/\">Supervised\/unsupervised classification<\/a>)<br><strong>79. Composite Bands [CB]<\/strong> &#8211; Combines single-band rasters into a composite raster for true color or false color display. (<a href=\"https:\/\/gisgeography.com\/arcgis-composite-bands\/\">Composite bands<\/a>)<br><strong>80. Pansharpening [PS]<\/strong> &#8211; Enhances spatial cell resolution by leveraging the panchromatic band.<br><strong>81. Atmosphere Correction [AC]<\/strong> &#8211; Corrects remote sensing imagery through scattering inherent in the atmosphere. (Dark object subtraction, radiative transfer models, <a href=\"https:\/\/gisgeography.com\/atmospheric-window\/\">atmosphere correction<\/a>)<br><strong>82. Segmentation [SG]<\/strong> &#8211; Grouping similar pixels from an image into vector objects to recognize objects and features. (Segment mean shift, <a href=\"https:\/\/gisgeography.com\/obia-object-based-image-analysis-geobia\/\">object-based image analysis<\/a>)<br><strong>83. Data Mining [DN]<\/strong> &#8211; Eliminates redundant data from variables that are highly correlated, aggregating essential information. (<a href=\"https:\/\/gisgeography.com\/principal-component-analysis-gis-redundant-data\/\">Principal component analysis<\/a>)<br><strong>84. Mensuration [ME]<\/strong> &#8211; Measures the geometry of two and three-dimensional features in an image. (Angles, height, perimeter, volume)<br><strong>85. Photogrammetry [PH]<\/strong> &#8211; Performs stereographic parallax from two or more vantage points of the same object to measure relief displacement. (<a href=\"https:\/\/gisgeography.com\/what-is-photogrammetry\/\">Photogrammetry<\/a>)<br><strong>86. Oblique [OB]<\/strong> &#8211; Collects images at an angle as opposed to a top-down orthographic perspective.<br><strong>87. Radar [RD]<\/strong> &#8211; Measures the backscatter of a sent microwave pulses to Earth whether it&#8217;s specular, diffuse, or double-bounce reflection. (<a href=\"https:\/\/gisgeography.com\/synthetic-aperture-radar-examples\/\">Synthetic aperture radar<\/a>)<\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Interpolation<\/h3>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"135\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-425x135.png\" alt=\"IDW Power 2\" class=\"wp-image-10651\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-425x135.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-300x96.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-678x216.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-768x245.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-50x16.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-200x64.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-550x175.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-115x37.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-850x271.png 850w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2-487x155.png 487w, https:\/\/gisgeography.com\/wp-content\/uploads\/2016\/05\/IDW-Power2.png 1165w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/figure>\n<\/div>\n\n\n<p><strong>88. Interpolation [IP]<\/strong> &#8211; Estimates unknown values using sampled locations by creating a prediction surface. (<a href=\"https:\/\/gisgeography.com\/inverse-distance-weighting-idw-interpolation\/\">IDW<\/a>, spline, trend)<br><strong>89. Kriging [KR]<\/strong> &#8211; Generates a probability and prediction surface by building a mathematical function through a semi-variogram. (<a href=\"https:\/\/gisgeography.com\/kriging-interpolation-prediction\/\">Kriging<\/a> and <a href=\"https:\/\/gisgeography.com\/semi-variogram-nugget-range-sill\/\">semi-variograms<\/a>, and <a href=\"https:\/\/gisgeography.com\/geostatistics\/\">geostatistics<\/a>)<br><strong>90. Kernel Density [KD]<\/strong> &#8211; Calculates hot and cold spots by applying a density-per-unit function (Heat map)<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Conclusion: The Periodic Table for Spatial Analysis<\/h3>\n\n\n\n<p>Spatial analysis may seem like <strong>alchemy<\/strong> to the inexperienced. But there is a <strong>science<\/strong> to it. By using spatial analysis, we can find patterns, quantify area, and predict outcomes with <strong>geography<\/strong> being the common link of it all.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Periodic Table for Spatial Analysis lists 90 tools for quantifying, finding patterns, and predicting outcomes in a geographic context.<\/p>\n","protected":false},"author":2,"featured_media":60699,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_kad_post_transparent":"default","_kad_post_title":"default","_kad_post_layout":"default","_kad_post_sidebar_id":"","_kad_post_content_style":"default","_kad_post_vertical_padding":"default","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[90],"tags":[448,447],"class_list":["post-50083","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-gis-analysis","tag-raster-tools","tag-vector-tools"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>The Periodic 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