Item talk:Q228579

{

 "@context": "http://schema.org/",
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 "url": "https://www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-foundation-remote-sensing-phenology",
 "headline": "NDVI, the Foundation for Remote Sensing Phenology",
 "datePublished": "November 27, 2018",
 "author": [
   {
     "@type": "Person",
     "name": "Jesslyn Brown",
     "url": "https://www.usgs.gov/staff-profiles/jesslyn-brown",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-9976-1998"
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   }
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 "description": [
   {
     "@type": "TextObject",
     "text": "By transforming raw satellite data into NDVI values, researchers can create images and other products that give a rough measure of vegetation type, amount, and condition on land surfaces around the world. NDVI is especially useful for continental- to global-scale vegetation monitoring because it can compensate for changing illumination conditions, surface slope, and viewing angle. That said, NDVI does tend to saturate over dense vegetation and is sensitive to underlying soil color."
   },
   {
     "@type": "TextObject",
     "text": "Remote sensing phenology studies use data gathered by satellite sensors that measure wavelengths of light absorbed and reflected by green plants. Certain pigments in plant leaves strongly absorb wavelengths of visible (red) light. The leaves themselves strongly reflect wavelengths of near-infrared light, which is invisible to human eyes. As a plant canopy changes from early spring growth to late-season maturity and senescence, these reflectance properties also change."
   },
   {
     "@type": "TextObject",
     "text": "NDVI values can be averaged over time to establish \"normal\" growing conditions in a region for a given time of year. Further analysis can then characterize the health of vegetation in that place relative to the norm. When analyzed through time, NDVI can reveal where vegetation is thriving and where it is under stress, as well as changes in vegetation due to human activities such as deforestation, natural disturbances such as wild fires, or changes in plants' phenological stage."
   },
   {
     "@type": "TextObject",
     "text": "Many sensors carried aboard satellites measure red and near-infrared light waves reflected by land surfaces. Using mathematical formulas (algorithms), scientists transform raw satellite data about these light waves into vegetation indices. A vegetation index is an indicator that describes the greenness \u2014 the relative density and health of vegetation \u2014 for each picture element, or pixel, in a satellite image."
   },
   {
     "@type": "TextObject",
     "text": "Although there are several vegetation indices, one of the most widely used is the Normalized Difference Vegetation Index (NDVI). NDVI values range from +1.0 to -1.0. Areas of barren rock, sand, or snow usually show very low NDVI values (for example, 0.1 or less). Sparse vegetation such as shrubs and grasslands or senescing crops may result in moderate NDVI values (approximately 0.2 to 0.5). High NDVI values (approximately 0.6 to 0.9) correspond to dense vegetation such as that found in temperate and tropical forests or crops at their peak growth stage."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Remote Sensing Phenology",
   "url": "https://www.usgs.gov/special-topics/remote-sensing-phenology"
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 "about": [
   {
     "@type": "Thing",
     "name": "Vegetation Indices"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   },
   {
     "@type": "Thing",
     "name": "Science Technology"
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   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "vegetation indices"
   },
   {
     "@type": "Thing",
     "name": "Maps and Mapping"
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   {
     "@type": "Thing",
     "name": "Climate"
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   {
     "@type": "Thing",
     "name": "earth resources observation and science center"
   },
   {
     "@type": "Thing",
     "name": "NDVI"
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   {
     "@type": "Thing",
     "name": "Water"
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     "name": "Remote Sensing Phenology"
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     "name": "Information Systems"
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     "@type": "Thing",
     "name": "Methods and Analysis"
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