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.)

  • obj (numpy.ndarray)

  • wsize (int, optional) – Size of the window surrounding the central pixel, defaults to 5.

Keyword Arguments
  • thrsnorain (float) –

  • tr1 (float) –

  • n_p (int) –

  • tr2 (float) –

  • rm_nans (bool) – True replaces nans with Inf False takes nans into acount

  • radial (bool) – True to use radial information only in filter_gabella_a.

  • cartesian (bool) – True if cartesian data are used, polar assumed if False.


output (numpy.ndarray) – boolean array with pixels identified as clutter set to True.


See Clutter detection using the Gabella approach.