ee.Kernel.chebyshev

Generates a distance kernel based on Chebyshev distance (greatest distance along any dimension).

UsageReturns
ee.Kernel.chebyshev(radius, units, normalize, magnitude)Kernel
ArgumentTypeDetails
radiusFloat

The 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: false

Normalize the kernel values to sum to 1.

magnitudeFloat, default: 1

Scale each value by this amount.

Examples

Code Editor (JavaScript)

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

/**
 * Output weights matrix
 *
 * [3, 3, 3, 3, 3, 3, 3]
 * [3, 2, 2, 2, 2, 2, 3]
 * [3, 2, 1, 1, 1, 2, 3]
 * [3, 2, 1, 0, 1, 2, 3]
 * [3, 2, 1, 1, 1, 2, 3]
 * [3, 2, 2, 2, 2, 2, 3]
 * [3, 3, 3, 3, 3, 3, 3]
 */