ee.Image.arrayMask

  • Image.arrayMask creates a new array image where each pixel is masked by another array image, keeping elements only where the mask is non-zero.

  • If the mask image has a single band, it is applied to all bands of the input image; otherwise, the mask and input images must have the same number of bands.

 Creates an array image where each array-valued pixel is masked with another array-valued pixel, retaining only the elements where the mask is non-zero. If the mask image has one band it will be applied to all the bands of 'input', otherwise they must have the same number of bands.

UsageReturns
Image.arrayMask(mask)Image
ArgumentTypeDetails
this: inputImageArray image to mask.
maskImageArray image to mask with.

Examples

Code Editor (JavaScript)

// A function to print arrays for a selected pixel in the following examples.
function sampArrImg(arrImg) {
  var point = ee.Geometry.Point([-121, 42]);
  return arrImg.sample(point, 500).first().get('array');
}

// Create a 1D array image with length 6.
var arrayImg1D = ee.Image([0, 1, 2, 4, 0, 5]).toArray();
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2, 4, 0, 5]

// Create a mask using a relational operator to mask values greater than 2.
var mask1D = arrayImg1D.lte(2);
print('1D mask for greater than value 2 (pixel)', sampArrImg(mask1D));
// [1, 1, 1, 0, 1, 0]

var arrayImg1DMask = arrayImg1D.arrayMask(mask1D);
print('1D array image mask (pixel)', sampArrImg(arrayImg1DMask));
// [0, 1, 2, 0]

// Self mask the 1D array image. Value zero will be masked out.
var arrayImg1DselfMask = arrayImg1D.arrayMask(arrayImg1D);
print('1D array image self mask (pixel)', sampArrImg(arrayImg1DselfMask));
// [1, 2, 4, 5]

// Create a 2D array image.
var arrayImg2D = arrayImg1D.arrayReshape(ee.Image([2, 3]).toArray(), 2);
print('2D 2x3 array image (pixel)', sampArrImg(arrayImg2D));
// [[0, 1, 2],
//  [4, 0, 5]]

// Slice out a row to use as a column mask.
var rowAsMaskForCols = arrayImg2D.arraySlice(0, 1, 2);
print('2D mask for cols (pixel)', sampArrImg(rowAsMaskForCols));
// [[4, 0, 5]]

var arrayImg2DMaskCols = arrayImg2D.arrayMask(rowAsMaskForCols);
print('2D array image cols masked (pixel)', sampArrImg(arrayImg2DMaskCols));
// [[0, 2],
//  [4, 5]]

// Slice out a column to use as a row mask.
var colAsMaskForRows = arrayImg2D.arraySlice(1, 1, 2);
print('2D mask for rows (pixel)', sampArrImg(colAsMaskForRows));
// [[1],
//  [0]]

var arrayImg2DMaskRows = arrayImg2D.arrayMask(colAsMaskForRows);
print('2D array image rows masked (pixel)', sampArrImg(arrayImg2DMaskRows));
// [[0, 1, 2]]

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 function to print arrays for a selected pixel in the following examples.
def samp_arr_img(arr_img):
  point = ee.Geometry.Point([-121, 42])
  return arr_img.sample(point, 500).first().get('array')

# Create a 1D array image with length 6.
array_img_1d = ee.Image([0, 1, 2, 4, 0, 5]).toArray()
display('1D array image (pixel):', samp_arr_img(array_img_1d))
# [0, 1, 2, 4, 0, 5]

# Create a mask using a relational operator to mask values greater than 2.
mask_1d = array_img_1d.lte(2)
display('1D mask for greater than value 2 (pixel):', samp_arr_img(mask_1d)
)
# [1, 1, 1, 0, 1, 0]

array_img1d_mask = array_img_1d.arrayMask(mask_1d)
display('1D array image mask (pixel):', samp_arr_img(array_img1d_mask))
# [0, 1, 2, 0]

# Self mask the 1D array image. Value zero will be masked out.
array_img_1d_self_mask = array_img_1d.arrayMask(array_img_1d)
display(
    '1D array image self mask (pixel):', samp_arr_img(array_img_1d_self_mask)
)
# [1, 2, 4, 5]

# Create a 2D array image.
array_img_2d = array_img_1d.arrayReshape(ee.Image([2, 3]).toArray(), 2)
display('2D 2x3 array image (pixel):', samp_arr_img(array_img_2d))
# [[0, 1, 2],
#  [4, 0, 5]]

# Slice out a row to use as a column mask.
row_as_mask_for_cols = array_img_2d.arraySlice(0, 1, 2)
display('2D mask for cols (pixel):', samp_arr_img(row_as_mask_for_cols))
# [[4, 0, 5]]

array_img_2d_mask_cols = array_img_2d.arrayMask(row_as_mask_for_cols)
display(
    '2D array image cols masked (pixel):', samp_arr_img(array_img_2d_mask_cols)
)
# [[0, 2],
#  [4, 5]]

# Slice out a column to use as a row mask.
col_as_mask_for_rows = array_img_2d.arraySlice(1, 1, 2)
display('2D mask for rows (pixel):', samp_arr_img(col_as_mask_for_rows))
# [[1],
#  [0]]

array_img_2d_mask_rows = array_img_2d.arrayMask(col_as_mask_for_rows)
display(
    '2D array image rows masked (pixel):', samp_arr_img(array_img_2d_mask_rows)
)
# [[0, 1, 2]]