GEMI

Summary

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.

Syntax

GEMI(raster, {nir_band_id}, {red_band_id})

Parameter	Explanation	Data Type
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

Parameter

Explanation

Data Type

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

Return value

Data Type	Explanation
Raster	The output raster object with the GEMI index values.

Code sample

GEMI example

Calculates the GEMI function for a Landsat 8 image.

import arcpy

GEMI_raster = arcpy.sa.GEMI("Landsat8.tif", 5, 4)