environmentaltools.spatiotemporal.indicators.neighbourhood_mean

environmentaltools.spatiotemporal.indicators.neighbourhood_mean(data_cube, size=3)

Calculate neighborhood mean value for each cell.

Applies a spatial moving average filter to compute the mean value within a specified neighborhood around each cell. This is useful for spatial smoothing and analyzing local context.

Parameters:

• data_cube (np.ndarray) – 3D array with shape (time, lat, lon) containing spatiotemporal data.

• size (int, optional) – Neighborhood size (e.g., 3 for 3x3 neighborhood). Default is 3.

Returns:

cube_filtered – 3D array with neighborhood means, same shape as input.

Return type:

np.ndarray

Notes

The function applies a uniform filter that computes the mean value within a square neighborhood of the specified size around each cell. Edge effects are handled using reflection mode.

Examples

>>> import numpy as np
>>> data_cube = np.random.random((10, 20, 20))
>>> smoothed = neighbourhood_mean(data_cube, size=5)