Las bandas de la imagen de entrada principal están disponibles con la función integrada b(), como b(0) o b("band_name").
Las variables de la expresión se interpretan como parámetros de imagen adicionales que se deben proporcionar en opt_map. Se puede acceder a las bandas de cada imagen de este tipo como image.band_name o image[0].
Tanto b() como image[] permiten varios argumentos para especificar varias bandas, como b(1, "name", 3). Si llamas a b() sin argumentos o usas una variable por sí sola, se devuelven todas las bandas de la imagen.
Si el resultado de una expresión es una sola banda, se le puede asignar un nombre con el operador "=" (p.ej., x = a + b).
Devuelve la imagen calculada por la expresión proporcionada.
Uso | Muestra |
---|---|
Image.expression(expression, map) | Imagen |
Argumento | Tipo | Detalles |
---|---|---|
esta: image | Imagen | Es la instancia de Image. |
expression | String | Es la expresión que se evaluará. |
map | Dictionary<Image>, opcional | Es un mapa de las imágenes de entrada disponibles por nombre. |
Ejemplos
Editor de código (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);
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