ee.Image.normalizedDifference

Computes the normalized difference between two bands. If the bands to use are not specified, uses the first two bands. The normalized difference is computed as (first − second) / (first + second). Note that the returned image band name is 'nd', the input image properties are not retained in the output image, and a negative pixel value in either input band will cause the output pixel to be masked. To avoid masking negative input values, use ee.Image.expression() to compute normalized difference.
Usage Returns
Image. normalizedDifference ( bandNames ) Image
Argument Type Details
this: input
Image The input image.
bandNames
List, default: null A list of names specifying the bands to use. If not specified, the first and second bands are used.

Examples

Code Editor (JavaScript)

 // A Landsat 8 surface reflectance image. 
 var 
  
 img 
  
 = 
  
 ee 
 . 
 Image 
 ( 
 'LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508' 
 ); 
 // Calculate normalized difference vegetation index: (NIR - Red) / (NIR + Red). 
 var 
  
 nirBand 
  
 = 
  
 'SR_B5' 
 ; 
 var 
  
 redBand 
  
 = 
  
 'SR_B4' 
 ; 
 var 
  
 ndvi 
  
 = 
  
 img 
 . 
 normalizedDifference 
 ([ 
 nirBand 
 , 
  
 redBand 
 ]); 
 // Display NDVI result on the map. 
 Map 
 . 
 setCenter 
 ( 
 - 
 122.148 
 , 
  
 37.377 
 , 
  
 11 
 ); 
 Map 
 . 
 addLayer 
 ( 
 ndvi 
 , 
  
 { 
 min 
 : 
  
 0 
 , 
  
 max 
 : 
  
 0.5 
 }, 
  
 'NDVI' 
 ); 

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

 import 
  
 ee 
 import 
  
 geemap.core 
  
 as 
  
 geemap 

Colab (Python)

 # A Landsat 8 surface reflectance image. 
 img 
 = 
 ee 
 . 
 Image 
 ( 
 'LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508' 
 ) 
 # Calculate normalized difference vegetation index: (NIR - Red) / (NIR + Red). 
 nir_band 
 = 
 'SR_B5' 
 red_band 
 = 
 'SR_B4' 
 ndvi 
 = 
 img 
 . 
 normalizedDifference 
 ([ 
 nir_band 
 , 
 red_band 
 ]) 
 # Display NDVI result on the map. 
 m 
 = 
 geemap 
 . 
 Map 
 () 
 m 
 . 
 set_center 
 ( 
 - 
 122.148 
 , 
 37.377 
 , 
 11 
 ) 
 m 
 . 
 add_layer 
 ( 
 ndvi 
 , 
 { 
 'min' 
 : 
 0 
 , 
 'max' 
 : 
 0.5 
 }, 
 'NDVI' 
 ) 
 m 
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