AI-generated Key Takeaways
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Generates a circle-shaped kernel for use in image processing.
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The kernel's radius can be specified in pixels or meters.
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Kernel values can be normalized to sum to 1 and scaled by a magnitude factor.
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Useful for operations like blurring or smoothing where a circular neighborhood is desired.
| Usage | Returns |
|---|---|
ee.Kernel.circle(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 circle kernel', ee.Kernel.circle({radius: 3})); /** * Output weights matrix (up to 1/1000 precision for brevity) * * [0.000, 0.000, 0.000, 0.034, 0.000, 0.000, 0.000] * [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] * [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] * [0.034, 0.034, 0.034, 0.034, 0.034, 0.034, 0.034] * [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] * [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] * [0.000, 0.000, 0.000, 0.034, 0.000, 0.000, 0.000] */
import ee import geemap.core as geemap
Colab (Python)
from pprint import pprint print('A circle kernel:') pprint(ee.Kernel.circle(**{'radius': 3}).getInfo()) # Output weights matrix (up to 1/1000 precision for brevity) # [0.000, 0.000, 0.000, 0.034, 0.000, 0.000, 0.000] # [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] # [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] # [0.034, 0.034, 0.034, 0.034, 0.034, 0.034, 0.034] # [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] # [0.000, 0.034, 0.034, 0.034, 0.034, 0.034, 0.000] # [0.000, 0.000, 0.000, 0.034, 0.000, 0.000, 0.000]