ee.Kernel.diamond

  • ee.Kernel.diamond generates a diamond-shaped boolean kernel.

  • The radius argument specifies the size of the kernel, and the units argument can be set to "pixels" or "meters".

  • The kernel values can be normalized to sum to 1 using the normalize argument and scaled by a factor using the magnitude argument.

  • Examples in both JavaScript and Python demonstrate how to use the ee.Kernel.diamond function and show the resulting kernel matrix.

 Generates a diamond-shaped boolean kernel.

UsageReturns
ee.Kernel.diamond(radius, units, normalize, magnitude)Kernel
ArgumentTypeDetails
radiusFloatThe radius of the kernel to generate.
unitsString, default: "pixels"The system of measurement for the kernel ('pixels' or 'meters'). If the kernel is specified in meters, it will resize when the zoom-level is changed.
normalizeBoolean, default: trueNormalize the kernel values to sum to 1.
magnitudeFloat, default: 1Scale each value by this amount.

Examples

Code Editor (JavaScript)

print('A diamond kernel', ee.Kernel.diamond({radius: 3}));

/**
 * Output weights matrix (up to 1/100 precision for brevity)
 *
 * [0.00, 0.00, 0.00, 0.04, 0.00, 0.00, 0.00]
 * [0.00, 0.00, 0.04, 0.04, 0.04, 0.00, 0.00]
 * [0.00, 0.04, 0.04, 0.04, 0.04, 0.04, 0.00]
 * [0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04]
 * [0.00, 0.04, 0.04, 0.04, 0.04, 0.04, 0.00]
 * [0.00, 0.00, 0.04, 0.04, 0.04, 0.00, 0.00]
 * [0.00, 0.00, 0.00, 0.04, 0.00, 0.00, 0.00]
 */

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)

from pprint import pprint

print('A diamond kernel:')
pprint(ee.Kernel.diamond(**{'radius': 3}).getInfo())

#  Output weights matrix (up to 1/100 precision for brevity)

#  [0.00, 0.00, 0.00, 0.04, 0.00, 0.00, 0.00]
#  [0.00, 0.00, 0.04, 0.04, 0.04, 0.00, 0.00]
#  [0.00, 0.04, 0.04, 0.04, 0.04, 0.04, 0.00]
#  [0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04]
#  [0.00, 0.04, 0.04, 0.04, 0.04, 0.04, 0.00]
#  [0.00, 0.00, 0.04, 0.04, 0.04, 0.00, 0.00]
#  [0.00, 0.00, 0.00, 0.04, 0.00, 0.00, 0.00]