ee.Kernel.diamond

AI-generated Key Takeaways

• 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.

Usage	Returns
ee.Kernel.diamond(radius, units, normalize, magnitude)	Kernel

Argument	Type	Details
radius	Float	The radius of the kernel to generate.
units	String, 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.
normalize	Boolean, default: true	Normalize the kernel values to sum to 1.
magnitude	Float, default: 1	Scale 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)

display('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]