GEMI
Résumé
Calculates the Global Environmental Monitoring Index (GEMI) from a multiband raster object and returns a raster object with the index values.
Discussion
The Global Environmental Monitoring Index (GEMI) method is a nonlinear vegetation index for global environmental monitoring from satellite imagery. It's similar to NDVI, but it's less sensitive to atmospheric effects. It is affected by bare soil; therefore, it's not recommended for use in areas of sparse or moderately dense vegetation.
\(GEMI = {(eta * (1 - (0.25 * eta)))} - \large \frac {(Red\ -\ 0.125)}{(1\ -\ Red)}\)
where:
\(eta = \large \frac {(2\ *\ (NIR^2 \ -\ Red^2) \ +\ (1.5\ *\ NIR) \ + \ (0.5\ *\ Red)}{(NIR\ +\ Red\ +\ 0.5)}\)
For information about other multiband raster indexes, see the Band Arithmetic raster function.
The referenced raster dataset for the raster object is temporary. To make it permanent, you can call the raster object's save method.
Syntaxe
GEMI(raster, {nir_band_id}, {red_band_id})
| Le paramètre | Explication | Type de données |
|---|---|---|
|
raster |
The input raster. |
Raster |
|
nir_band_id |
The band ID of the near-infrared band. The ID index uses one-based indexing. The default value is 4. |
Integer |
|
red_band_id |
The band ID of the red band. The ID index uses one-based indexing. The default value is 3. |
Integer |
Valeur de retour
| Type de données | Explication |
|---|---|
|
Raster |
The output raster object with the GEMI index values. |
Exemple de code
Calculates the GEMI function for a Landsat 8 image.
import arcpy
GEMI_raster = arcpy.sa.GEMI("Landsat8.tif", 5, 4)