{"id":422,"date":"2022-03-24T13:37:10","date_gmt":"2022-03-24T12:37:10","guid":{"rendered":"https:\/\/www.eovision.at\/esa-schoolatlas\/?page_id=422"},"modified":"2025-03-03T13:55:09","modified_gmt":"2025-03-03T12:55:09","slug":"indices","status":"publish","type":"page","link":"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/remotesensing\/indices\/","title":{"rendered":"Indices"},"content":{"rendered":"<h2><a class=\"glossaryLink\" title=\"Glossary: satellite\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;satellite&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;A free-flying object orbiting the Earth, another planet, or the sun.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/satellite\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Satellite<\/a> Data Interpretation &#x2013; Indices<\/h2>\n<p><iframe src=\"https:\/\/esa-schoolatlas.eu\/wp-content\/gismaps_maps\/rsp09_indices\/index.html\" width=\"100%\" height=\"670\"><\/iframe><\/p>\n<p>Interpreting satellite data to derive insights about Earth&#x2019;s surface features and changes is a complex task. Index-based analysis has emerged as a powerful tool to extract information from satellite data. Examples of indices, derived from combinations of spectral bands, highlight specific features, patterns, and environmental conditions:<\/p>\n<p><strong>Vegetation<\/strong>: Vegetation indices are fundamental in monitoring plant health, <a class=\"glossaryLink\" title=\"Glossary: Biomass\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Biomass&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;1. Ecology: total mass of living biological organisms in a given area or ecosystem2. Energy production: biological mass used as a renewable energy source.3. Satellite technology: Part of the Earth Explorer Mission of ESA, created to observe and analyse the world&#x2019;s forests using radar technology.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/biomass\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">biomass<\/a>, and <a class=\"glossaryLink\" title=\"Glossary: land cover\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;land cover&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;The characteristics of a land surface as determined by its spectral signature (the unique way in which a given type of land cover reflects and absorbs light).&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/land-cover\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">land cover<\/a> changes. Indices like the Normalised Difference <a class=\"glossaryLink\" title=\"Glossary: Vegetation Index\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Vegetation Index&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Measure of the greenness and vigour of the vegetation in a region.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/vegetation-index\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Vegetation Index<\/a> (<a class=\"glossaryLink\"  title=\"Glossary: NDVI\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;NDVI&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Normalized Difference Vegetation Index: A model for converting satellite-based measurements into surface vegetation types. The NDVI uses a complex ratio of reflectance in the red and near-infrared portions of the spectrum to accomplish this. It is a quantity that measures greenness and vigour of vegetation. NDVI = (NIR - Red)\/(NIR + Red).&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/ndvi\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>NDVI<\/a>) use the contrast between the <a class=\"glossaryLink\" title=\"Glossary: reflectance\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;reflectance&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;The proportion of irradiated electromagnetic radiation reflected by a surface.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/reflectance\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">reflectance<\/a> in the red and near-infrared bands to quantify vegetation density. High NDVI values typically indicate healthy and dense vegetation, while lower values suggest stressed or sparse vegetation. These indices are crucial for applications ranging from agriculture monitoring to ecosystem health assessments. <\/p>\n<p><strong><a class=\"glossaryLink\"  title=\"Glossary: soil\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;soil&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Biologically active, porous medium that covers the uppermost layer of Earth&lsquo;s crust.&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/soil\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>Soil<\/a><\/strong>: The Normalised Soil <a class=\"glossaryLink\" title=\"Glossary: Moisture Index\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Moisture Index&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Method to assess the water content of the surface layer of Earth based on satellite data.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/moisture-index\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Moisture Index<\/a> (NSMI) gives insight into the water balance of the soils, important information e.g. for agricultural activities.<\/p>\n<p><strong><a class=\"glossaryLink\" title=\"Glossary: urbanisation\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;urbanisation&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Increase in the proportion of people living in towns and cities due to people moving from rural areas to urban areas.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/urbanisation\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Urbanisation<\/a><\/strong>: Urbanisation indices help analyse and monitor the extent and characteristics of urban areas within satellite imagery. The Urban Heat Island Index (UHII), for example, compares the temperature of urban and rural areas, highlighting the increased heat in urban environments. Other indices, like the Normalised Difference Built-Up Index (NDBI), focus on the built-up areas within the landscape, aiding in urban planning and infrastructure development studies.<\/p>\n<p><strong>Water<\/strong>: Satellite data are used to assess water quality through specific indices. The Normalised Difference <a class=\"glossaryLink\" title=\"Glossary: Water Index\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Water Index&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Measure of the proportion of an area covered by water.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/water-index\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Water Index<\/a> (<a class=\"glossaryLink\"  title=\"Glossary: NDWI\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;NDWI&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Normalized Difference Water Index: A method used to identify water bodies in satellite image data based on the information contained in the green and near infrared (NIR) bands. NDWI = (Green - NIR)\/(Green + NIR).&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/ndwi\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>NDWI<\/a>) is used to identify surface water bodies, while indices like the Water Quality Index (WQI) use multiple bands to assess parameters such as <a class=\"glossaryLink\" title=\"Glossary: chlorophyll\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;chlorophyll&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Molecule in green plants giving them their colour. It allows plants to absorb energy from the sun as they undergo the process of photosynthesis.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/chlorophyll\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">chlorophyll<\/a> concentration and sediment loads, offering insights into <a class=\"glossaryLink\" title=\"Glossary: aquatic\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;aquatic&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;related to water.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/aquatic\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">aquatic<\/a> ecosystems and water resource management. <\/p>\n<p><strong>Burned Area<\/strong>: Monitoring and assessing burned areas and wildfires are critical applications of satellite data. Indices like the Normalised Burn Ratio (NBR) highlight changes in vegetation cover after a fire. With them, analysts can quantify the severity and extent of the burned area, aiding in post-fire recovery planning and ecological restoration. <\/p>\n<p>&#xA0;<\/p>\n<h3>Exercises<\/h3>\n<ul>\n<li><strong>Satellite Map:<\/strong>\n<ul>\n<li>Use the layer selector to select the NDVI (normalised difference vegetation index) derived from the <a class=\"glossaryLink\" title=\"Glossary: Sentinel\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Sentinel&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Series of six different Earth Observation satellite types under responsibility of ESA in the Copernicus programme.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/sentinel\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Sentinel<\/a>-2 data. Compare with the true colour image and try to identify the <a class=\"glossaryLink\" title=\"Glossary: land use\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;land use&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;The characteristics of a land surface as determined by its use (the unique way in which a given type of land is &#x2013; or is not &#x2013; exploited by man).&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/land-use\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">land use<\/a> and landcover classes in the region.<\/li>\n<li>Find features with low\/high NDVI and identify the respective land cover using the true colour image. Where is the NDVI low, where is it high? Do your findings fit with your expectations?<\/li>\n<li>Select now the NSMI (normalised soil moisture index) and repeat what you did with the NDVI.<\/li>\n<li>Take a special look at agricultural land, both with and without vegetation. Which parts appear to be driest (red colours in the NSMI)?<\/li>\n<li>Look at built-up areas. The colours differ between yellow and red, i.e. between low and very low soil moisture. What does this tell us about the density of settlements?<\/li>\n<li>Look at the NDWI (normalised water index) showing water bodies in blue and compare with the true colour image. Are the water bodies identified correctly?<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><strong><a class=\"glossaryLink\" title=\"Glossary: Copernicus\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Copernicus&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Former name GMES (Global Monitoring for Environment and Security), the EU&#x2019;s Copernicus Earth observation programme, comprising in-situ elements (measurement tools) and the space segment (satellites).&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/copernicus\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Copernicus<\/a> Browser:<\/strong>\n<ul>\n<li>Open the case study area in the <a href=\"https:\/\/link.dataspace.copernicus.eu\/czyo\" target=\"_blank\" rel=\"noopener\">Copernicus Browser<\/a>.<\/li>\n<li>Find the most recent Sentinel-2 dataset covering the area displayed in the satellite map.<\/li>\n<li>Select a natural colour representation.<\/li>\n<li>Can you identify additional, recent changes in the area?<\/li>\n<li>Select one by one the index visualisations offered by Copernicus Browser (NDVI, NDWI, <a class=\"glossaryLink\"  title=\"Glossary: NDSI\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;NDSI&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Normalized Difference Soil Index: Method to assess the proportion of bare soil of a surface based on near infrared and shortwave infrared data: NDSI = (NIR - SWIR)\/(NIR + SWIR). Sometimes NDSI can refer to a Snow Index or a Salinity Index.&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/ndsi\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>NDSI<\/a>, Moisture Index). Zoom into different sections of the area and check, where these indices can help to discriminate important land cover classes.<\/li>\n<li>For advanced readers: Select the <strong>custom visualisation<\/strong> and there the tab &laquo;Index&raquo;. Try to define indices with <a class=\"glossaryLink\"  title=\"Glossary: band\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;band&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;A region of the electromagnetic spectrum to which a remote sensor responds; a multispectral sensor makes measurements in a number of spectral bands.&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/band\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>band<\/a> combinations of your own. What are your findings with respect to the representation of different landcover classes (water, agricultural land, built-up land, etc.)?<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&#xA0;<\/p>\n<h3>Links and Sources<\/h3>\n<table style=\"background-color: #444444;\">\n<tbody>\n<tr>\n<td style=\"vertical-align: middle; padding-left: 10px;\"><strong>Downloads:<\/strong><\/td>\n<td><\/td>\n<\/tr><tr>\n<td align=\"center\"><img decoding=\"async\" class=\"wp-image-1439\" src=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-150x150.png\" alt=\"\" width=\"25\" height=\"25\" srcset=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-150x150.png 150w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-152x150.png 152w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-80x80.png 80w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-300x300.png 300w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4.png 320w\" sizes=\"(max-width: 25px) 100vw, 25px\"\/><\/td>\n<td>\nPDF document of the case study (includes exercises):<br>\n<a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/RSP09_4_EN_RemoteSensing_Indices.pdf\" target=\"_blank\" rel=\"noopener\">English<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/RSP09_4_DE_RemoteSensing_Indices.pdf\" target=\"_blank\" rel=\"noopener\"> German<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/RSP09_4_FR_RemoteSensing_Indices.pdf\" target=\"_blank\" rel=\"noopener\"> French<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/RSP09_4_IT_RemoteSensing_Indices.pdf\" target=\"_blank\" rel=\"noopener\"> Italian<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/RSP09_4_ES_RemoteSensing_Indices.pdf\" target=\"_blank\" rel=\"noopener\"> Spanish<\/a>\n<\/td>\n<\/tr>\n<tr>\n<td align=\"center\">\n<img decoding=\"async\" class=\"wp-image-1439\" src=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-150x150.png\" alt=\"\" width=\"25\" height=\"25\" srcset=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-150x150.png 150w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-152x150.png 152w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-80x80.png 80w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4-300x300.png 300w, https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/uploads\/sites\/7\/2023\/11\/pdf-icon-4.png 320w\" sizes=\"(max-width: 25px) 100vw, 25px\"\/>\n<\/td>\n<td>\nThis case study is covered on page 20 of the printed <a class=\"glossaryLink\"  title=\"Glossary: ESA\"  aria-describedby=\"tt\"  data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;ESA&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;The European Space Agency&lt;\/div&gt;\"  href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/esa\/\"  target=\"_blank\"  data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]'  tabindex='0' role='link'>ESA<\/a> Schoolatlas &ndash; download the PDF document of the page:<br>\n<a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/ESA_Schoolatlas_EN_Page20.pdf\" target=\"_blank\" rel=\"noopener\">English<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/ESA_Schoolatlas_DE_Page20.pdf\" target=\"_blank\" rel=\"noopener\">German<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/ESA_Schoolatlas_FR_Page20.pdf\" target=\"_blank\" rel=\"noopener\">French<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/ESA_Schoolatlas_IT_Page20.pdf\" target=\"_blank\" rel=\"noopener\">Italian<\/a>, <a href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/wp-content\/gismaps_maps\/rsp09_indices\/ESA_Schoolatlas_ES_Page20.pdf\" target=\"_blank\" rel=\"noopener\">Spanish<\/a>\n<\/td>\n<\/tr>\n<\/tbody><\/table>\n\n\n\n\n<table style=\"background-color: #444444;\">\n<tbody>\n<tr>\n<td style=\"vertical-align: middle; padding-left: 10px;\"><strong>Links:<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"padding-left: 10px;\">\n<ul>\n<li><a href=\"https:\/\/www.esa.int\/Education\/1._Introduction\" target=\"_blank\">https:\/\/www.esa.int\/Education\/1._Introduction<\/a> &#x2013; ESA&#x2019;s <a class=\"glossaryLink\" title=\"Glossary: Earth observation\" aria-describedby=\"tt\" data-cmtooltip=\"&lt;div class=glossaryItemTitle&gt;Earth observation&lt;\/div&gt;&lt;div class=glossaryItemBody&gt;Observation of the Earth from space, mostly based on satellites.&lt;\/div&gt;\" href=\"https:\/\/esa-schoolatlas.eu\/esa-schoolatlas\/es\/glossary\/earth-observation\/\" target=\"_blank\" data-gt-translate-attributes='[{\"attribute\":\"data-cmtooltip\", \"format\":\"html\"}]' tabindex=\"0\" role=\"link\">Earth observation<\/a> course for secondary schools<\/li>\n<li><a href=\"https:\/\/eos.com\/make-an-analysis\/ndvi\/\" target=\"_blank\">https:\/\/eos.com\/make-an-analysis\/ndvi\/<\/a> &#x2013; basic description of NDVI and its use in agriculture <\/li>\n<li><a href=\"http:\/\/www.eo4geo.eu\/training\/sentinel-2-data-and-vegetation-indices\/\" target=\"_blank\">http:\/\/www.eo4geo.eu\/training\/sentinel-2-data-and-vegetation-indices\/<\/a> &#x2013; EO4GEO lecture on Sentinel-2 and Vegetation Indices<br>\n<\/li><\/ul><\/td><\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"<p>Satellite Data Interpretation &#x2013; Indices Interpreting satellite data to derive insights about Earth&#x2019;s surface features and changes is a complex task. Index-based analysis has emerged as a powerful tool to extract information from satellite data. Examples of indices, derived from combinations of spectral bands, highlight specific features, patterns, and environmental conditions: Vegetation: Vegetation indices are [&#x2026;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":404,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-422","page","type-page","status-publish","hentry"],"translation":{"provider":"WPGlobus","version":"3.0.0","language":"es","enabled_languages":["en","es","de","fr","it"],"languages":{"en":{"title":true,"content":true,"excerpt":false},"es":{"title":false,"content":false,"excerpt":false},"de":{"title":true,"content":true,"excerpt":false},"fr":{"title":false,"content":false,"excerpt":false},"it":{"title":false,"content":false,"excerpt":false}}},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>- ESA Schoolatlas<\/title>\n<meta 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