- pysteps.feature.tstorm.detection(input_image, max_num_features=None, minref=35, maxref=48, mindiff=6, minsize=50, minmax=41, mindis=10, output_feat=False, time='000000000')#
This function detects thunderstorms using a multi-threshold approach. It is recommended to use a 2-D Cartesian maximum reflectivity composite, however the function will process any 2-D array. The thunderstorm cell detection requires both scikit-image and pandas.
input_image (array-like) – Array of shape (m,n) containing input image, usually maximum reflectivity in dBZ with a resolution of 1 km. Nan values are ignored.
max_num_features (int, optional) – The maximum number of cells to detect. Set to None for no restriction. If specified, the most significant cells are chosen based on their area.
minref (float, optional) – Lower threshold for object detection. Lower values will be set to NaN. The default is 35 dBZ.
maxref (float, optional) – Upper threshold for object detection. Higher values will be set to this value. The default is 48 dBZ.
mindiff (float, optional) – Minimal difference between two identified maxima within same area to split area into two objects. The default is 6 dBZ.
minsize (float, optional) – Minimal area for possible detected object. The default is 50 pixels.
minmax (float, optional) – Minimum value of maximum in identified objects. Objects with a maximum lower than this will be discarded. The default is 41 dBZ.
mindis (float, optional) – Minimum distance between two maxima of identified objects. Objects with a smaller distance will be merged. The default is 10 km.
output_feat (bool, optional) – Set to True to return only the cell coordinates.
time (string, optional) – Date and time as string. Used to label time in the resulting dataframe. The default is ‘000000000’.
cells_id (pandas dataframe) – Pandas dataframe containing all detected cells and their respective properties corresponding to the input image. Columns of dataframe: ID - cell ID, time - time stamp, x - array of all x-coordinates of cell, y - array of all y-coordinates of cell, cen_x - x-coordinate of cell centroid, cen_y - y-coordinate of cell centroid, max_ref - maximum (reflectivity) value of cell, cont - cell contours
labels (array-like) – Array of shape (m,n), grid of labelled cells.