{"id":56589,"date":"2019-06-14T10:37:32","date_gmt":"2019-06-14T10:37:32","guid":{"rendered":"https:\/\/av3aerovisual.com\/indices-de-vegetacion\/"},"modified":"2021-10-15T00:56:14","modified_gmt":"2021-10-15T00:56:14","slug":"vegetation-indices","status":"publish","type":"post","link":"https:\/\/av3aerovisual.com\/en\/vegetation-indices\/","title":{"rendered":"Vegetation index"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">The vegetation indices are visual representations of the reflectance of plants. They work by combining two or more wavelengths of the electromagnetic spectrum (green, red, infrared, near infrared, red edge, blue, etc &#8230;).<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Each one is designed to accentuate specific properties of the analyzed vegetation: variation of nutrients, water stress, biomass and use of light, are some examples of properties that can be analyzed with vegetation indexes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&nbsp;There are more than 150 indexes published in the scientific literature and are grouped into the following categories:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><b>Green reflectance<\/b><\/li>\n<li style=\"font-weight: 400;\"><b>Light Efficiency<\/b><\/li>\n<li style=\"font-weight: 400;\"><b>Nitrogen in foliage<\/b><\/li>\n<li style=\"font-weight: 400;\"><b>Carbon stroke<\/b><\/li>\n<li style=\"font-weight: 400;\"><b>Pigmentation<\/b><\/li>\n<li style=\"font-weight: 400;\"><b>Water content<\/b><\/li>\n<\/ul>\n\n\n<h4 class=\"wp-block-heading\"><strong><strong>Some of the most known vegetation indexes are:<\/strong><\/strong><\/h4>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndvi-indices-de-vegetacion-blog-av3-01.png\" alt=\"\" class=\"wp-image-54062\" width=\"550\" height=\"600\" srcset=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndvi-indices-de-vegetacion-blog-av3-01.png 550w, https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndvi-indices-de-vegetacion-blog-av3-01-275x300.png 275w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong><strong>Normalized Difference Vegetation Index<\/strong><\/strong><\/h4>\n\n\n\n<p><strong>NDVI=<\/strong> (NIR-RED) \/ (NIR+RED)<\/p>\n\n\n\n<p><strong>Range:<\/strong> -1 a 1<\/p>\n\n\n\n<p><strong>Propiedades:<\/strong> Differentiation of green and healthy vegetation of yellowish and stressed vegetation. Observation of areas with normal percentages of chlorophyll and photosynthesis. Information on relative biomass and foliage.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/gndvi-indices-de-vegetacion-blog-av3-01.png\" alt=\"\" class=\"wp-image-54063\" width=\"550\" height=\"600\" srcset=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/gndvi-indices-de-vegetacion-blog-av3-01.png 550w, https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/gndvi-indices-de-vegetacion-blog-av3-01-275x300.png 275w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Green Normalized Difference Vegetation Index<\/strong><\/h4>\n\n\n\n<p><strong>GNDVI=<\/strong> (NIR-GREEN) \/ (NIR+GREEN)<\/p>\n\n\n\n<p><strong>Range:<\/strong> -1 a 1<\/p>\n\n\n\n<p><strong>Properties:<\/strong> Similar to NDVI with an even greater focus on chlorophyll. Designed for vegetation with more foliage. Emphasize more on poor vegetation in chlorophyll and soil or non-photosynthetic areas.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndre-indices-de-vegetacion-blog-av3-01.png\" alt=\"\" class=\"wp-image-54074\" width=\"550\" height=\"600\" srcset=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndre-indices-de-vegetacion-blog-av3-01.png 550w, https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/ndre-indices-de-vegetacion-blog-av3-01-275x300.png 275w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Normalized Difference Red Edge<\/strong><\/h4>\n\n\n\n<p><strong>NDRE=<\/strong> (NIR-RE) \/ (NIR+RE)<\/p>\n\n\n\n<p><strong>Range:<\/strong> -1 a 1<\/p>\n\n\n\n<p><strong>Properties:<\/strong> More suitable for making measurement in late stages of a crop because of its focus on the differences between vegetation and soil.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/mcari-indices-de-vegetacion-blog-av3-01.png\" alt=\"\" class=\"wp-image-54075\" width=\"550\" height=\"600\" srcset=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/mcari-indices-de-vegetacion-blog-av3-01.png 550w, https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/mcari-indices-de-vegetacion-blog-av3-01-275x300.png 275w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Modified Chlorophyll Absorption Ratio Index<\/strong><\/h4>\n\n\n\n<p><strong>MCARI=<\/strong> [(p700-p670)-0.2(p700-p550)]*(p700\/p670)<\/p>\n\n\n\n<p><strong>Range:<\/strong> -1 a 1<\/p>\n\n\n\n<p><strong>Properties:<\/strong> More suitable for crops with greater amount of foliage when focusing on subtle differences of areas with higher and lower chlorophyll.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/sipi2-indices-de-vegetacion-blog-av3-01.png\" alt=\"\" class=\"wp-image-54077\" width=\"550\" height=\"600\" srcset=\"https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/sipi2-indices-de-vegetacion-blog-av3-01.png 550w, https:\/\/av3aerovisual.com\/wp-content\/uploads\/2019\/06\/sipi2-indices-de-vegetacion-blog-av3-01-275x300.png 275w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Structure Intensive Pigment Index 2<\/strong><\/h4>\n\n\n\n<p><strong>SIPI2=<\/strong> (800nm-505nm)\/(800nm-690nm)<\/p>\n\n\n\n<p><strong>Range:<\/strong> -1 a 1<\/p>\n\n\n\n<p><strong>Properties:<\/strong> More suitable for forest analysis or crops with high foliage variation.<\/p>\n\n\n\n<p>It is important to understand that the images generated from vegetation indices are visual representations of information; therefore, it&#8217;s not the colors that matter, but the numerical range of the indices. The colorimetry of the images can change, the important thing is to understand the scale of the indices and how they relate to a crop and its conditions.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\"><strong><strong>REFERENCES<\/strong><\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li><strong><a href=\"https:\/\/www.ispag.org\/\" target=\"_blank\" rel=\"noreferrer noopener\">ISPA<\/a><\/strong><\/li><li><strong><a href=\"https:\/\/www.harrisgeospatial.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">HARRIS GEOSPATIAL<\/a><\/strong><\/li><li><strong><a href=\"https:\/\/www.mdpi.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">MDPI<\/a><\/strong><\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\"><strong><strong>OUR EXPERTS WILL ANALYZE YOUR FIELD TO DETERMINE<\/strong><\/strong><\/h5>\n\n\n\n<h5 class=\"wp-block-heading\"><strong><strong>WHAT INDICES OF VEGETATION ARE THE MOST SUITABLE TO SATISFY YOUR NEEDS.<\/strong><\/strong><\/h5>\n\n\n\n<p><\/p>\n\n\n\n<p style=\"text-align: center;\"><a href=\"https:\/\/av3aerovisual.com\/en\/contacto\/#cotiza\"><button type=\"button\">ASK FOR A QUOTATION<\/button><\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"tel:442 129 7892\"><button type=\"button\">CALL US<\/button><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Vegetation indices are visual representations of plant reflectance. Nutrient variation, water stress, biomass, light use, are some examples of properties that can be analyzed with vegetation indices.<\/p>\n","protected":false},"author":2,"featured_media":56394,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[436],"tags":[485,486,729],"class_list":["post-56589","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-precision-agriculture","tag-agriculture","tag-precision-agriculture","tag-vegetation-index"],"_links":{"self":[{"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/posts\/56589","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/comments?post=56589"}],"version-history":[{"count":21,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/posts\/56589\/revisions"}],"predecessor-version":[{"id":60468,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/posts\/56589\/revisions\/60468"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/media\/56394"}],"wp:attachment":[{"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/media?parent=56589"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/categories?post=56589"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/av3aerovisual.com\/en\/wp-json\/wp\/v2\/tags?post=56589"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}