What is the difference between NDVI and EVI?

What is the difference between NDVI and EVI?

Whereas the Normalized Difference Vegetation Index (NDVI) is chlorophyll sensitive, the EVI is more responsive to canopy structural variations, including leaf area index (LAI), canopy type, plant physiognomy, and canopy architecture. EVI is currently distributed for free by the USGS LP DAAC.

How is EVI calculated?

These enhancements allow for index calculation as a ratio between the R and NIR values, while reducing the background noise, atmospheric noise, and saturation in most cases. In Landsat 4-7, EVI = 2.5 * ((Band 4 – Band 3) / (Band 4 + 6 * Band 3 – 7.5 * Band 1 + 1)).

Can enhanced vegetation index be negative?

It can be seen from its mathematical definition that the NDVI of an area containing a dense vegetation canopy will tend to positive values (say 0.3 to 0.8) while clouds and snow fields will be characterized by negative values of this index.

What do the values in an NDVI image represent?

The most common measurement is called the Normalized Difference Vegetation Index (NDVI). Very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate and tropical rainforests (0.6 to 0.8).

What is the range of enhanced vegetation index?

-1 to 1
The Enhanced Vegetation Index was invented by Liu and Huete to simultaneously correct NDVI results for atmospheric influences and soil background signals, especially in areas of dense canopy. The value range for EVI is -1 to 1, and for healthy vegetation it varies between 0.2 and 0.8.

How do you interpret NDWI values?

High values of NDWI (in blue) correspond to high vegetation water content and to high vegetation fraction cover. Low NDWI values (in red) correspond to low vegetation water content and low vegetation fraction cover. In period of water stress, NDWI will decrease.

How do you calculate vegetation index?

Formula of SAVI vegetation index:

1. SAVI = ((NIR – Red) / (NIR + Red + L)) x (1 + L)
2. ARVI = (NIR – (2 * Red) + Blue) / (NIR + (2 * Red) + Blue)
3. EVI = 2.5 * ((NIR – Red) / ((NIR) + (C1 * Red) – (C2 * Blue) + L))
4. GCI = (NIR) / (Green) – 1.
5. SIPI = (NIR – Blue) / (NIR – Red)
6. NBR = (NIR – SWIR) / (NIR + SWIR)

How is the enhanced vegetation index ( EVI ) developed?

The enhanced vegetation index (EVI) was developed as an alternative vegetation index to address some of the limitations of the NDVI. The EVI was specifically developed to: correct for canopy background signals.

Which is better to measure vegetation NDVI or Evi?

Derived from state-of-the-art satellite data provided by the MODIS instrument, EVI improves on NDVI’s spatial resolution, is more sensitive to differences in heavily vegetated areas (as seen here in the Yucatan Peninsula), and better corrects for atmospheric haze as well as the land surface beneath the vegetation.

How does the enhanced vegetation index work on Landsat?

It incorporates an “L” value to adjust for canopy background, “C” values as coefficients for atmospheric resistance, and values from the blue band (B). These enhancements allow for index calculation as a ratio between the R and NIR values, while reducing the background noise, atmospheric noise, and saturation in most cases.

What does Evi stand for on Landsat 4?

Landsat Surface Reflectance-derived Enhanced Vegetation Index (EVI) are available for Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) scenes that can be successfully processed to Landsat Level-2 Surface Reflectance products.