ee.Kernel.cross
Generates a cross-shaped boolean kernel.
| Usage | Returns |
|---|
ee.Kernel.cross(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
print('A cross kernel', ee.Kernel.cross({radius: 3}));
/**
* Output weights matrix (up to 1/1000 precision for brevity)
*
* [0.076, 0.000, 0.000, 0.000, 0.000, 0.000, 0.076]
* [0.000, 0.076, 0.000, 0.000, 0.000, 0.076, 0.000]
* [0.000, 0.000, 0.076, 0.000, 0.076, 0.000, 0.000]
* [0.000, 0.000, 0.000, 0.076, 0.000, 0.000, 0.000]
* [0.000, 0.000, 0.076, 0.000, 0.076, 0.000, 0.000]
* [0.000, 0.076, 0.000, 0.000, 0.000, 0.076, 0.000]
* [0.076, 0.000, 0.000, 0.000, 0.000, 0.000, 0.076]
*/
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
from pprint import pprint
print('A cross kernel:')
pprint(ee.Kernel.cross(**{'radius': 3}).getInfo())
# Output weights matrix (up to 1/1000 precision for brevity)
# [0.076, 0.000, 0.000, 0.000, 0.000, 0.000, 0.076]
# [0.000, 0.076, 0.000, 0.000, 0.000, 0.076, 0.000]
# [0.000, 0.000, 0.076, 0.000, 0.076, 0.000, 0.000]
# [0.000, 0.000, 0.000, 0.076, 0.000, 0.000, 0.000]
# [0.000, 0.000, 0.076, 0.000, 0.076, 0.000, 0.000]
# [0.000, 0.076, 0.000, 0.000, 0.000, 0.076, 0.000]
# [0.076, 0.000, 0.000, 0.000, 0.000, 0.000, 0.076]
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["Generates a kernel with values arranged in a cross shape, useful for image processing operations."],["The kernel's size is determined by the `radius` parameter, and values can be normalized and scaled."],["By default, the kernel values are normalized to sum to 1 and scaled by 1."],["The kernel can be defined in either 'pixels' or 'meters', affecting its behavior when the zoom level changes."]]],["The core functionality is generating a cross-shaped boolean kernel using `ee.Kernel.cross`. Users specify the `radius` to define the kernel's size. They can also choose the `units` ('pixels' or 'meters'), `normalize` (to sum values to 1), and the `magnitude` to scale values. This method returns a `Kernel` object. An example shows how a radius of 3 results in a 7x7 weight matrix where only cross-shaped positions are populated.\n"]]