{"id":15776,"date":"2020-11-27T05:38:39","date_gmt":"2020-11-27T11:38:39","guid":{"rendered":"http:\/\/gisgeography.com\/?p=15776"},"modified":"2024-05-19T05:33:36","modified_gmt":"2024-05-19T10:33:36","slug":"synthetic-aperture-radar-examples","status":"publish","type":"post","link":"https:\/\/gisgeography.com\/synthetic-aperture-radar-examples\/","title":{"rendered":"Learn Synthetic Aperture Radar (SAR) by Example"},"content":{"rendered":"<style>.kb-image15776_c86e3e-7e .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<figure class=\"wp-block-kadence-image kb-image15776_c86e3e-7e size-medium_large\"><img loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"339\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-768x339.png\" alt=\"Synthetic Aperture Radar SAR Feature\" class=\"kb-img wp-image-61479\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-768x339.png 768w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-300x132.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-678x299.png 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-50x22.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-80x35.png 80w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-200x88.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-425x188.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-550x243.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-115x51.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature-360x159.png 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Synthetic-Aperture-Radar-SAR-Feature.png 850w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \/><\/figure>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--30);padding-bottom:var(--wp--preset--spacing--30)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">Synthetic Aperture Radar (SAR) Basics<\/h2>\n\n\n\n<p>Synthetic Aperture Radar (SAR) is an emerging technology in remote sensing.<\/p>\n\n\n\n<p>In fact, Sentinel-1 is equipped with this <a href=\"https:\/\/gisgeography.com\/passive-active-sensors-remote-sensing\/\">active type of sensor<\/a>. Likewise, Radarsat and TerraSAR use synthetic aperture radar.<\/p>\n\n\n\n<p>The main advantage of this technology is that it can synthetically produce higher-resolution images in any weather condition and even at night.<\/p>\n\n\n\n<p>Today, we don&#8217;t intend on getting into precise details about how this technology works. Instead, we will <strong>interpret SAR imagery<\/strong> with basic examples and give some real-world applications.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">SAR&#8217;s Bat-Like Capabilities<\/h2>\n\n\n\n<p>It&#8217;s said that synthetic aperture radar is similar to how bats use echolocation to navigate in a cave.<\/p>\n\n\n\n<p>When bats fly in a cave, they use sound to navigate. Generally, they create sound waves from 50 to 120 dB. When this sound bounces off a wall and returns to the bat, it understands distance <strong>based on the echo<\/strong>.<\/p>\n\n\n\n<p>In general, the same principles apply to SAR. The satellite <strong>sends<\/strong> microwave pulses to Earth. The pulse <strong>returns<\/strong> back to the satellite and the sensor makes an image from the returned echoes.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"639\" height=\"250\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa.jpg\" alt=\"L band radar africa\" class=\"wp-image-16046\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa.jpg 639w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-300x117.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-50x20.jpg 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-200x78.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-425x166.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-550x215.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-115x45.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-150x60.jpg 150w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/l-band-radar-africa-396x155.jpg 396w\" sizes=\"auto, (max-width: 639px) 100vw, 639px\" \/><\/figure>\n\n\n\n<p>Generally, synthetic aperture radar is side-looking. This means they don\u2019t look completely down at Nadir but <strong>at an angle<\/strong>. There are advantages to this type of viewing angle which I will mention below.<\/p>\n\n\n\n<p>As mentioned earlier, microwave radar can be seen at <strong>night and through clouds and smoke<\/strong>. At any time of the day or in any type of weather condition, SAR works.<\/p>\n\n\n\n<p>Actually, longer wavelengths can penetrate clouds better and even the ground. For example, L-band (~24 cm) radar has longer wavelengths than C-band (~6 cm) and X-band (~3cm). Learn more about <a href=\"https:\/\/gisgeography.com\/radar-bands\/\">Radar bands here<\/a>.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">Types of Radar Scattering<\/h2>\n\n\n\n<p>Side-looking radar interacts with different types of terrain. The 3 main <strong>types of scattering<\/strong> mechanisms are:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Specular<\/li>\n\n\n\n<li>Diffuse<\/li>\n\n\n\n<li>Double-bounce<\/li>\n<\/ul>\n\n\n\n<p>First, we will provide a schematic for each type of scattering. After, we will give an interpretation of where each type of scattering occurs.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Smooth Surface<\/h3>\n\n\n\n<p>Smooth Surface reflection comes from flat terrains like roads or water. For this type of scattering, very little energy of the transmitted pulse returns to the sensor.<\/p>\n\n\n<style>.kb-image15776_6b09ac-ae.kb-image-is-ratio-size, .kb-image15776_6b09ac-ae .kb-image-is-ratio-size{max-width:300px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_6b09ac-ae.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_6b09ac-ae .kb-image-is-ratio-size{align-self:unset;}.kb-image15776_6b09ac-ae figure{max-width:300px;}.kb-image15776_6b09ac-ae .image-is-svg, .kb-image15776_6b09ac-ae .image-is-svg img{width:100%;}.kb-image15776_6b09ac-ae .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image15776_6b09ac-ae\"><figure class=\"aligncenter size-medium-extra\"><img loading=\"lazy\" decoding=\"async\" width=\"360\" height=\"283\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface-360x283.jpg\" alt=\"Smooth Surface\" class=\"kb-img wp-image-90460\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface-360x283.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface-300x236.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface-200x157.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface-115x90.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SmoothSurface.jpg 425w\" sizes=\"auto, (max-width: 360px) 100vw, 360px\" \/><\/figure><\/div>\n\n\n\n<p>In this example, pixels will typically appear <strong>black<\/strong> typically with values less than -20dB. Smooth surface reflection resembles the behavior of a mirror. It can also be helpful in the detection of flooded lands and water characteristics.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Rough Surface<\/h3>\n\n\n\n<p>Rough surface scattering such as plowed farm fields and vegetation. Scattering goes in all directions diffusely. For example, typical pixel values will be greater than -20dB and in <strong>grey<\/strong>. <\/p>\n\n\n<style>.kb-image15776_5529d2-05 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image15776_5529d2-05\"><figure class=\"aligncenter size-medium\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"248\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface-300x248.jpg\" alt=\"Rough Surface\" class=\"kb-img wp-image-90461\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface-300x248.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface-200x166.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface-115x95.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface-360x298.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/Rough-Surface.jpg 401w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure><\/div>\n\n\n\n<p>This type of scattering is common in natural environments. It is also useful in distinguishing between different land cover features, aiding in applications like agriculture monitoring and land use classification.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Volume Scattering<\/h3>\n\n\n\n<p>Volume scattering occurs when the radar waves penetrate an object that is not completely solid but has many internal layers or scatterers. For example, forests scatter waves in many directions as they hit different parts of the tree.<\/p>\n\n\n<style>.kb-image15776_abb783-65.kb-image-is-ratio-size, .kb-image15776_abb783-65 .kb-image-is-ratio-size{max-width:300px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_abb783-65.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_abb783-65 .kb-image-is-ratio-size{align-self:unset;}.kb-image15776_abb783-65 figure{max-width:300px;}.kb-image15776_abb783-65 .image-is-svg, .kb-image15776_abb783-65 .image-is-svg img{width:100%;}.kb-image15776_abb783-65 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image15776_abb783-65\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"499\" height=\"539\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering.jpg\" alt=\"Volume Scattering\" class=\"kb-img wp-image-90465\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering.jpg 499w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering-278x300.jpg 278w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering-185x200.jpg 185w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering-393x425.jpg 393w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering-115x124.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/VolumeScattering-360x389.jpg 360w\" sizes=\"auto, (max-width: 499px) 100vw, 499px\" \/><\/figure><\/div>\n\n\n\n<p>Volume scattering can tell you about the structure and density of an object. In the case of a forest, it can tell us something about the vegetation density, the type of trees, and even the health of the forest.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Double-bounce<\/h3>\n\n\n\n<p>Often, <strong>Double bounce<\/strong> occurs off structures and man-made objects. The reflected pulse hits one surface after the other and back to the sensor. For example, typical pixel values will appear <strong>white<\/strong> with values greater than -10dB. <\/p>\n\n\n<style>.kb-image15776_70840a-4d.kb-image-is-ratio-size, .kb-image15776_70840a-4d .kb-image-is-ratio-size{max-width:300px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_70840a-4d.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image15776_70840a-4d .kb-image-is-ratio-size{align-self:unset;}.kb-image15776_70840a-4d figure{max-width:300px;}.kb-image15776_70840a-4d .image-is-svg, .kb-image15776_70840a-4d .image-is-svg img{width:100%;}.kb-image15776_70840a-4d .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image15776_70840a-4d\"><figure class=\"aligncenter size-medium-large\"><img loading=\"lazy\" decoding=\"async\" width=\"355\" height=\"425\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-355x425.jpg\" alt=\"Double Bounce\" class=\"kb-img wp-image-90463\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-355x425.jpg 355w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-251x300.jpg 251w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-167x200.jpg 167w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-460x550.jpg 460w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-115x137.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce-360x430.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/DoubleBounce.jpg 491w\" sizes=\"auto, (max-width: 355px) 100vw, 355px\" \/><\/figure><\/div>\n\n\n\n<p>This is particularly important in radar imaging and urban environments, where the double bounce effect helps in the mapping of infrastructure.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">SAR Image Interpretation<\/h2>\n\n\n\n<p>Now that you know the basics of synthetic aperture radar, let&#8217;s look at a SAR image with these types of scattering. In this Radarsat-2 example, the image clearly shows all three types of backscatter.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"350\" height=\"250\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example.png\" alt=\"Radarsat2 example: double bounce, specular reflection and diffuse backscatter\" class=\"wp-image-2728\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example.png 350w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example-300x214.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example-50x36.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example-200x143.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example-115x82.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2014\/05\/Radarsat2-Example-217x155.png 217w\" sizes=\"auto, (max-width: 350px) 100vw, 350px\" \/><figcaption class=\"wp-element-caption\">Radarsat-2 image: double bounce, specular reflection, and diffuse backscatter<\/figcaption><\/figure>\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Specular Reflection<\/h3>\n\n\n\n<p>In this scene, there is a river that flows in the east-west direction. As shown in the schematic above, very little energy reflects back to the radar sensor. In this case, the pixel is <strong>dark with a low dB<\/strong>.<\/p>\n\n\n\n<p>This can also be seen in the southeast portion with the road\/airport paved surface. Again, this is a specular reflection off a smooth surface.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Double-Bounce Scattering<\/h3>\n\n\n\n<p>On the other hand, the bright white in the center of the image can be interpreted as an urban feature. The radar is receiving double-bounce backscatter, meaning the transmitted pulses are returning to the sensor.<\/p>\n\n\n\n<p>It\u2019s unclear at this scale what this object is but it\u2019s due to <strong>double-bounce returns<\/strong>. Because of its values greater than -10dB, pixels will appear as a bright white.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h3 class=\"wp-block-heading\">Diffuse Scattering<\/h3>\n\n\n\n<p>Finally, the majority of the radar image is <strong>rough surface scattering<\/strong>. You have a bit of specular and double-bounce scattering.<\/p>\n\n\n\n<p>This may be from annual cropland, vegetation, grasses, or other features. It is diffuse scattering because there\u2019s not a high or low amount of backscatter in the image.<\/p>\n\n\n<style>.kb-image15776_fc1110-7f .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<figure class=\"wp-block-kadence-image kb-image15776_fc1110-7f size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"678\" height=\"296\" src=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-678x296.jpg\" alt=\"SAR Polarization\" class=\"kb-img wp-image-90468\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-678x296.jpg 678w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-300x131.jpg 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-200x87.jpg 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-425x186.jpg 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-550x240.jpg 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-115x50.jpg 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization-360x157.jpg 360w, https:\/\/gisgeography.com\/wp-content\/uploads\/2020\/11\/SAR-Polarization.jpg 710w\" sizes=\"auto, (max-width: 678px) 100vw, 678px\" \/><\/figure>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">Synthetic Aperture Radar Use Cases<\/h2>\n\n\n\n<p>How can we apply these SAR concepts to real-world applications? There are <a href=\"https:\/\/gisgeography.com\/remote-sensing-applications\/\">hundreds of remote sensing applications<\/a>. Likewise, SAR has applications in the environment, safety, military, and more. Actually, the first one shares the same acronym as SAR (search and rescue).<\/p>\n\n\n\n<p>In <strong>search and rescue missions<\/strong>, weather conditions are often poor. In the case of forest fires, smoke could completely block visibility. Because microwave SAR is not affected by these types of conditions, rescuers use it to find man-made objects on the ground. Specifically, it looks for double-bounce scattering where the crash site occurred. Or even where <strong>flooding<\/strong> occurs, if there is a specular reflection (dark pixels).<\/p>\n\n\n\n<p>Scientists use synthetic aperture radar to <strong>estimate surface elevation<\/strong> with the <a href=\"https:\/\/www2.jpl.nasa.gov\/srtm\/instrumentinterfmore.html\" target=\"_blank\" rel=\"noreferrer noopener\">Space Shuttle Radar Topography Mission inSAR<\/a>. This satellite used interferometry (InSAR) generating one of the most accurate <a href=\"https:\/\/gisgeography.com\/free-global-dem-data-sources\/\">elevation models<\/a> of the whole globe. In addition, scientists use InSAR for terrain displacement based on phase differences.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"425\" height=\"197\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-425x197.png\" alt=\"Radar Interferometry InSAR Terrain Displacement\" class=\"wp-image-16047\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-425x197.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-300x139.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-50x23.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-200x93.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-550x255.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-115x53.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement-335x155.png 335w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/Radar-Interferometry-InSAR-Terrain-Displacement.png 564w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><figcaption class=\"wp-element-caption\">Radar Interferometry InSAR &#8211; Terrain Displacement<\/figcaption><\/figure>\n<\/div>\n\n\n<p>As shown above, SAR is about understanding surface characteristics based on backscatter. That&#8217;s why we use SAR during <strong>oil spills<\/strong> and to understand ocean waves. During an oil spill, oil floats on water-suppressing waves. This creates a smoother surface, appearing dark in the radar image. But if you were <strong>searching for a ship<\/strong> in the Arctic, you&#8217;d look for double-bounce or bright pixels in a SAR image.<\/p>\n\n\n\n<p>Lastly, microwave radar is sensitive to the dielectric constant in features. This is why researchers are trying to study <strong>soil moisture<\/strong> using synthetic aperture radar. In agriculture, farmers can use this to understand wetness in the first few centimeters of a bare soil profile. Even for <strong>mapping wetlands<\/strong>, scientists use the Touzi decomposition technique.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">A Little Deeper in the Technology<\/h2>\n\n\n\n<p>Polarization refers to the <strong>orientation of the radar wave<\/strong> from the SAR antenna. Both electric and magnetic lines of force are at right angles to each other, but it&#8217;s the electric field that determines the direction of polarization of the wave. Synthetic Aperture Radar uses an antenna that can transmit in either the horizontal (H) or vertical (V) polarization.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"220\" src=\"http:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-300x220.png\" alt=\"electromagnetic waves hh vv hv vh\" class=\"wp-image-16049\" srcset=\"https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-300x220.png 300w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-50x37.png 50w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-200x147.png 200w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-425x312.png 425w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-550x404.png 550w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-115x84.png 115w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh-211x155.png 211w, https:\/\/gisgeography.com\/wp-content\/uploads\/2017\/08\/electromagnetic-waves-hh-vv-hv-vh.png 640w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n<\/div>\n\n\n<p>When the electromagnetic wave scatters from a target, the polarisation state of an electromagnetic wave can change. When the sensor receives the returning wave, it measures the degree of change in polarization from the target. For example, it can either be H or V polarization or both simultaneously.<\/p>\n\n\n\n<p>For single-polarization, these are typical transmit and receive pairs.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>HH &#8211; for horizontal transmit and horizontal receive<\/li>\n\n\n\n<li>VV &#8211; for vertical transmit and vertical receive<\/li>\n\n\n\n<li>HV &#8211; for horizontal transmit and vertical receive<\/li>\n\n\n\n<li>VH &#8211; for vertical transmit and horizontal receive<\/li>\n<\/ul>\n\n\n\n<p>The advantage is that you can infer more information about surface characteristics. For example, we can use decomposition techniques like Freeman-Durden to obtain how much surface, double-bounce, and volume scattering in a SAR image.<\/p>\n\n\n\n<p>Finally, it&#8217;s <strong>synthetic aperture<\/strong> because it can create higher resolution images. Because it receives backscatter along the length of the synthetic aperture radar, it can synthetically generate a higher-resolution image for a point target on Earth.<\/p>\n\n\n\n<p>The entire length of the synthetic aperture radar has the backscatter information for the point target. When all the backscatter information is merged, it&#8217;s like a &#8220;synthetic aperture&#8221;.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group\" style=\"padding-top:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--40)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\">Summary: Synthetic Aperture Radar (SAR)<\/h2>\n\n\n\n<p>Without experience in radar, it may look like a bunch of pixels. You don\u2019t get a pretty picture used on a map.<\/p>\n\n\n\n<p>Regardless, radar images can be noisy and often require smoothing. But using decomposition techniques and a bit of SAR interpretation, suddenly SAR images become a valuable tool.<\/p>\n\n\n\n<p>If you want to try to use synthetic aperture radar, take a look at our <a href=\"https:\/\/gisgeography.com\/free-satellite-imagery-data-list\/\">list of 15 free satellite imagery sources<\/a>.<\/p>\n\n\n\n<p>And don&#8217;t forget, there is <a href=\"https:\/\/gisgeography.com\/open-source-remote-sensing-software-packages\/\">open source remote sensing software<\/a> like the <a href=\"https:\/\/sentinel.esa.int\/web\/sentinel\/toolboxes\/sentinel-1\" target=\"_blank\" rel=\"noopener noreferrer\">Sentinel-1 toolbox<\/a> to help analyze and visualize SAR imagery.<\/p>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Synthetic Aperture Radar (SAR) is an emerging technology in remote sensing with the advantage to see in any weather condition and even at night.<\/p>\n","protected":false},"author":2,"featured_media":16043,"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":[92],"tags":[459],"class_list":["post-15776","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-remote-sensing","tag-remote-sensing-types"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Learn Synthetic Aperture 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