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)

display('A Roberts kernel:', ee.Kernel.roberts())

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

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