AI-generated Key Takeaways
-
The
ee.Kernel.squarefunction generates a square-shaped boolean kernel. -
The function takes arguments for
radius,units,normalize, andmagnitudeto customize the kernel. -
The
radiusargument determines the size of the square kernel. -
The
unitsargument specifies whether the radius is in pixels or meters. -
The
normalizeandmagnitudearguments control the normalization and scaling of the kernel values.
| Usage | Returns |
|---|---|
ee.Kernel.square(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 square kernel' , ee . Kernel . square ({ radius : 3 })); /** * Output weights matrix (up to 1/100 precision for brevity) * * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] * [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] */
import ee import geemap.core as geemap
Colab (Python)
display ( 'A square kernel:' , ee . Kernel . square ( ** { 'radius' : 3 })) # Output weights matrix (up to 1/100 precision for brevity) # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02] # [0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02]
