In ArcMap you can rightclick on the raster layer and under the Source tab it will give you the statistics. It will give you the min, max, mean, sum and standard deviation for example. This will result in a value range of 0–200 and fit within an 8-bit structure, which can easily be rendered with a specific color ramp or color map. Video 33This video shows a simple demo of the Raster Calculator that comes with the ESRI Spatial Analyst extension. For example the Raster layer statistics algorithm under QGIS geoalgorithms -> Raster tools is such a tool that does the job. The equation that is used to generate the output is as follows: NDVI = ((IR - R)/(IR + R)) * 100 + 100 Moderate values (0.2 to 0.3) represent shrub and grassland, while high values (0.6 to 0.8) indicate temperate and tropical rainforests. Very low values (0.1 and below) of NDVI correspond to barren areas of rock, sand, or snow. This index outputs values between -1.0 and 1.0, mostly representing greenness, where any negative values are mainly generated from clouds, water, and snow, and values near zero are mainly generated from rock and bare soil. IR = pixel values from the infrared band.The documented and default NDVI equation is as follows: NDVI = ((IR - R)/(IR + R)) The negative values represent clouds, water, and snow, and values near zero represent rock and bare soil. The NDVI process creates a single-band dataset that mainly represents greenery. Clouds, water, and snow show better reflection in the visible range than in the near-infrared range, while the difference is almost zero for rock and bare soil. When leaves are water stressed, diseased, or dead, they become more yellow and reflect significantly less in the near-infrared range. Green leaves commonly show better reflection in the near-infrared wavelength range than in visible wavelength ranges. The differential reflection in the red and infrared (IR) bands enables you to monitor density and intensity of green vegetation growth using the spectral reflectivity of solar radiation. The NDVI is preferred for global vegetation monitoring because it helps compensate for changing illumination conditions, surface slope, aspect, and other extraneous factors (Lillesand 2004). This index takes advantage of the contrast of the characteristics of two bands from a multispectral raster dataset-the chlorophyll pigment absorptions in the red band and the high reflectivity of plant materials in the near-infrared (NIR) band.Īn NDVI is often used worldwide to monitor drought, monitor and predict agricultural production, assist in predicting hazardous fire zones, and map desert encroachment. The Normalized Difference Vegetation Index (NDVI) is a standardized index allowing you to generate an image displaying greenness (relative biomass).
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