wradlib.classify.filter_gabella#
- wradlib.classify.filter_gabella(obj, *, wsize=5, **kwargs)[source]#
- wradlib.classify.filter_gabella(obj: DataArray, **kwargs)
Clutter identification filter developed by [Gabella et al., 2002].
This is a two-part identification algorithm using echo continuity and minimum echo area to distinguish between meteorological (rain) and non- meteorological echos (ground clutter etc.)
- Parameters:
obj (
numpy.ndarray
)wsize (
int
, optional) – Size of the window surrounding the central pixel, defaults to 5.
- Keyword Arguments:
- Returns:
output (
numpy.ndarray
) – boolean array with pixels identified as clutter set to True.
See also
Examples