ee.Kernel.roberts

AI-generated Key Takeaways

• The ee.Kernel.roberts() function generates a 2x2 Roberts edge-detection kernel.

• The magnitude argument scales the kernel values, and the normalize argument can normalize them to sum to 1.

• The examples show how to use the ee.Kernel.roberts() function in both the Code Editor (JavaScript) and Colab (Python).

Generates a 2x2 Roberts edge-detection kernel.

Usage	Returns
ee.Kernel.roberts(magnitude, normalize)	Kernel

Argument	Type	Details
magnitude	Float, default: 1	Scale each value by this amount.
normalize	Boolean, default: false	Normalize the kernel values to sum to 1.

Examples

Code Editor (JavaScript)

print('A Roberts kernel', ee.Kernel.roberts());

/**
 * Output weights matrix; center is position [1,1]
 *
 * [1,  0]
 * [0, -1]
 */

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 Roberts kernel:')
pprint(ee.Kernel.roberts().getInfo())

#  Output weights matrix; center is position [1,1]

#  [1,  0]
#  [0, -1]