ee.Image.expression

Evaluates an arithmetic expression on an image, possibly involving additional images.

The bands of the primary input image are available using the built-in function b(), as b(0) or b('band_name').

Variables in the expression are interpreted as additional image parameters which must be supplied in opt_map. The bands of each such image can be accessed like image.band_name or image[0].

Both b() and image[] allow multiple arguments, to specify multiple bands, such as b(1, 'name', 3). Calling b() with no arguments, or using a variable by itself, returns all bands of the image.

If the result of an expression is a single band, it can be assigned a name using the '=' operator (e.g.: x = a + b).

Returns the image computed by the provided expression.

UsageReturns
Image.expression(expression, map)Image
ArgumentTypeDetails
this: imageImageThe Image instance.
expressionStringThe expression to evaluate.
mapDictionary<Image>, optionalA map of input images available by name.

Examples

Code Editor (JavaScript)

// The following expressions calculate the normalized difference vegetation
// index (NDVI): (NIR - Red) / (NIR + Red).
// NIR is Landsat 8 L2 band 'SR_B5', the 4th band index.
// Red is Landsat 8 L2 band 'SR_B4', the 3rd band index.

// A Landsat 8 L2 surface reflectance image.
var img = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508');

// Visualization parameters for NDVI.
var ndviVis = {min: 0, max: 0.5};

// Expression using image band indices.
var bandIndexExp = '(b(4) - b(3)) / (b(4) + b(3))';
var bandIndexImg = img.expression(bandIndexExp).rename('NDVI');
Map.setCenter(-122.14, 37.38, 11);
Map.addLayer(bandIndexImg, ndviVis, 'NDVI 1');

// Expression using image band names.
var bandNameExp = '(b("SR_B5") - b("SR_B4")) / (b("SR_B5") + b("SR_B4"))';
var bandNameImg = img.expression(bandNameExp).rename('NDVI');
Map.addLayer(bandNameImg, ndviVis, 'NDVI 2');

// Expression using named variables.
var namedVarsExp = '(NIR - Red) / (NIR + Red)';
var namedVarsImg = ee.Image().expression({
  expression: namedVarsExp,
  map: {
    NIR: img.select('SR_B5'),
    Red: img.select('SR_B4')
  }
}).rename('NDVI');
Map.addLayer(namedVarsImg, ndviVis, 'NDVI 3');

// Expression using named variables with image band access by dot notation.
var namedVarsDotExp = '(ls8.SR_B5 - ls8.SR_B4) / (ls8.SR_B5 + ls8.SR_B4)';
var namedVarsDotImg = ee.Image().expression({
  expression: namedVarsDotExp,
  map: {ls8: img}
}).rename('NDVI');
Map.addLayer(namedVarsDotImg, ndviVis, 'NDVI 4');

// Expressions can use arithmetic operators (+ - * / % **), relational
// operators (== != < > <= >=), logical operators (&& || ! ^), the ternary
// operator (condition ? ifTrue : ifFalse), and a subset of JavaScript Math
// functions. Math functions are called by name directly, they are not accessed
// from the Math object (e.g., sqrt() instead of Math.sqrt()).
var jsMathExp = 'c = sqrt(pow(a, 2) + pow(b, 2))';
var jsMathImg = ee.Image().expression({
  expression: jsMathExp,
  map: {
    a: ee.Image(5),
    b: img.select('SR_B2')
  }
});
Map.addLayer(jsMathImg, {min: 5000, max: 20000}, 'Hypotenuse', false);

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)

# The following expressions calculate the normalized difference vegetation
# index (NDVI): (NIR - Red) / (NIR + Red).
# NIR is Landsat 8 L2 band 'SR_B5', the 4th band index.
# Red is Landsat 8 L2 band 'SR_B4', the 3rd band index.

# A Landsat 8 L2 surface reflectance image.
img = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508')

# Visualization parameters for NDVI.
ndvi_vis = {'min': 0, 'max': 0.5}

# Expression using image band indices.
band_index_exp = '(b(4) - b(3)) / (b(4) + b(3))'
band_index_img = img.expression(band_index_exp).rename('NDVI')
m = geemap.Map()
m.set_center(-122.14, 37.38, 11)
m.add_layer(band_index_img, ndvi_vis, 'NDVI 1')

# Expression using image band names.
band_name_exp = '(b("SR_B5") - b("SR_B4")) / (b("SR_B5") + b("SR_B4"))'
band_name_img = img.expression(band_name_exp).rename('NDVI')
m.add_layer(band_name_img, ndvi_vis, 'NDVI 2')

# Expression using named variables.
named_vars_exp = '(NIR - Red) / (NIR + Red)'
named_vars_img = (
    ee.Image()
    .expression(
        expression=named_vars_exp,
        opt_map={'NIR': img.select('SR_B5'), 'Red': img.select('SR_B4')},
    )
    .rename('NDVI')
)
m.add_layer(named_vars_img, ndvi_vis, 'NDVI 3')

# Expression using named variables with image band access by dot notation.
named_vars_dot_exp = '(ls8.SR_B5 - ls8.SR_B4) / (ls8.SR_B5 + ls8.SR_B4)'
named_vars_dot_img = (
    ee.Image()
    .expression(expression=named_vars_dot_exp, opt_map={'ls8': img})
    .rename('NDVI')
)
m.add_layer(named_vars_dot_img, ndvi_vis, 'NDVI 4')

# Expressions can use arithmetic operators (+ - * / % **), relational
# operators (== != < > <= >=), logical operators (&& || ! ^), the ternary
# operator (condition ? ifTrue : ifFalse), and a subset of JavaScript Math
# functions. Math functions are called by name directly, they are not accessed
# from the Math object (e.g., sqrt() instead of Math.sqrt()).
js_math_exp = 'c = sqrt(pow(a, 2) + pow(b, 2))'
js_math_img = ee.Image().expression(
    expression=js_math_exp, opt_map={'a': ee.Image(5), 'b': img.select('SR_B2')}
)
m.add_layer(js_math_img, {'min': 5000, 'max': 20000}, 'Hypotenuse', False)
m