ee.Image.arrayFlatten

Converts a single-band image of equal-shape multidimensional pixels to an image of scalar pixels, with one band for each element of the array.

Usage	Returns
Image.arrayFlatten(coordinateLabels, separator)	Image

Argument	Type	Details
this: image	Image	Image of multidimensional pixels to flatten.
coordinateLabels	List	Name of each position along each axis. For example, 2x2 arrays with axes meaning 'day' and 'color' could have labels like [['monday', 'tuesday'], ['red', 'green']], resulting in band names'monday_red', 'monday_green', 'tuesday_red', and 'tuesday_green'.
separator	String, default: "_"	Separator between array labels in each band name.

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');
}

// A 1D array image.
var arrayImg1D = ee.Image([0, 1, 2]).toArray();
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2]

// Define image band names for a 1D array image with 3 rows. You are labeling
// all rows and columns using a list of lists; the 1st sub list defines labels
// for array rows and the 2nd (if applicable) defines labels for array columns.
var bandNames1D = [['row0', 'row1', 'row2']];

// Flatten the 1D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 0 columns,
// so the result will be a 3-band image.
var imgFrom1Darray = arrayImg1D.arrayFlatten(bandNames1D);
print('Image from 1D array', imgFrom1Darray);

// Make a 2D array image by repeating the 1D array on 2-axis.
var arrayImg2D = arrayImg1D.arrayRepeat(1, 2);
print('2D array image (pixel)', sampArrImg(arrayImg2D));
// [[0, 0],
//  [1, 1],
//  [2, 2]]

// Define image band names for a 2D array image with 3 rows and 2 columns.
// Recall that you are labeling all rows and columns using a list of lists;
// The 1st sub list defines labels for array rows and the 2nd (if applicable)
// defines labels for array columns.
var bandNames2D = [['row0', 'row1', 'row2'], ['col0', 'col1']];

// Flatten the 2D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 2 columns,
// so the result will be a 6-band image.
var imgFrom2Darray = arrayImg2D.arrayFlatten(bandNames2D);
print('Image from 2D array', imgFrom2Darray);

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')

# A 1D array image.
array_img_1d = ee.Image([0, 1, 2]).toArray()
print('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())
# [0, 1, 2]

# Define image band names for a 1D array image with 3 rows. You are labeling
# all rows and columns using a list of lists; the 1st sub list defines labels
# for array rows and the 2nd (if applicable) defines labels for array columns.
band_names_1d = [['row0', 'row1', 'row2']]

# Flatten the 1D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 0 columns,
# so the result will be a 3-band image.
img_from_1d_array = array_img_1d.arrayFlatten(band_names_1d)
print('Image from 1D array:', img_from_1d_array.getInfo())

# Make a 2D array image by repeating the 1D array on 2-axis.
array_img_2d = array_img_1d.arrayRepeat(1, 2)
print('2D array image (pixel):', samp_arr_img(array_img_2d).getInfo())
# [[0, 0],
#  [1, 1],
#  [2, 2]]

# Define image band names for a 2D array image with 3 rows and 2 columns.
# Recall that you are labeling all rows and columns using a list of lists;
# The 1st sub list defines labels for array rows and the 2nd (if applicable)
# defines labels for array columns.
band_names_2d = [['row0', 'row1', 'row2'], ['col0', 'col1']]

# Flatten the 2D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 2 columns,
# so the result will be a 6-band image.
img_from_2d_array = array_img_2d.arrayFlatten(band_names_2d)
print('Image from 2D array:', img_from_2d_array.getInfo())