AI-generated Key Takeaways
- 
          The ee.Kernel.crossfunction generates a cross-shaped boolean kernel.
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          The function takes arguments for radius,units,normalize, andmagnitude.
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          The generated kernel is a weights matrix representing the cross shape. 
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          Examples are provided for both JavaScript and Python environments. 
| 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
Code Editor (JavaScript)
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] */
import ee import geemap.core as geemap
Colab (Python)
display('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]