ee.Image.toArray

  • Image.toArray() converts an image's band values into an array for each pixel, creating an "array image".

  • The optional axis argument controls the dimension along which the bands are concatenated in the array image.

  • Array images can be displayed and inspected, with the first element of the array represented visually.

  • This function enables analysis and manipulation of multi-band images by treating pixel values as arrays.

 Concatenates pixels from each band into a single array per pixel. The result will be masked if any input bands are masked.

UsageReturns
Image.toArray(axis)Image
ArgumentTypeDetails
this: imageImageImage of bands to convert to an array per pixel. Bands must have scalar pixels, or array pixels with equal dimensionality.
axisInteger, default: 0Axis to concatenate along; must be at least 0 and at most the dimension of the inputs. If the axis equals the dimension of the inputs, the result will have 1 more dimension than the inputs.

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 3-band image of constants.
var img = ee.Image([0, 1, 2]);
print('3-band image', img);

// Convert the 3-band image to an array image. The resulting array image has a
// single band named "array". The "array" band stores the per-pixel band values
// from the input ee.Image as a 1D array.
var arrayImg1D = img.toArray();
print('1D array image', arrayImg1D);

// Sample a single pixel to see its 1D array using the `sampArrImg` function
// defined above. Similar arrays are present for all pixels in a given array
// image; looking at just one helps conceptualize the structure.
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2]

// Array images can be displayed to the Code Editor map and queried with the
// inspector tool. Per-pixel, the first element in the array is shown.
// Single-band grayscale is used to represent the data. Style parameters `min`
// and `max` are valid. Styling the layer with the Code Editor's layer
// visualization tool is invalid.
Map.addLayer(arrayImg1D, {min: 0, max: 2}, 'Image array');

// Create a 2D array image by concatenating the values in a 1D array image
// along the 1-axis using `toArray(1)`. For a 3D array, apply `toArray(2)` to
// the result.
var arrayImg2D = arrayImg1D.toArray(1);
print('2D array image (pixel)', sampArrImg(arrayImg2D));
// [[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')


# A 3-band image of constants.
img = ee.Image([0, 1, 2])
display('3-band image', img)

# Convert the 3-band image to an array image. The resulting array image has a
# single band named "array". The "array" band stores the per-pixel band values
# from the input ee.Image as a 1D array.
array_img_1_d = img.toArray()
display('1D array image', array_img_1_d)

# Sample a single pixel to see its 1D array using the `samp_arr_img` function
# defined above. Similar arrays are present for all pixels in a given array
# image looking at just one helps conceptualize the structure.
display('1D array image (pixel)', samp_arr_img(array_img_1_d))
# [0, 1, 2]

# Array images can be displayed to the Code Editor map and queried with the
# inspector tool. Per-pixel, the first element in the array is shown.
# Single-band grayscale is used to represent the data. Style parameters `min`
# and `max` are valid. Styling the layer with the Code Editor's layer
# visualization tool is invalid.
m = geemap.Map()
m.add_layer(array_img_1_d, {'min': 0, 'max': 2}, 'Image array')
display(m)

# Create a 2D array image by concatenating the values in a 1D array image
# along the 1-axis using `toArray(1)`. For a 3D array, apply `toArray(2)` to
# the result.
array_img_2_d = array_img_1_d.toArray(1)
display('2D array image (pixel)', samp_arr_img(array_img_2_d))
# [[0],
#  [1],
#  [2]]