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Segmentation outputs a mask (`iris.cube.Cube` and in the future `xarray.DataArray`) with the same dimensions as the input field, where each segmented area has the same ID as its corresponding feature (see `feature` column in :doc:`feature_detection_output`). Note that there are some cases in which a feature is not attributed to a segmented area associated with it (see :doc:`features_without_segmented_area`).
Segmentation also outputs the same `pandas` dataframe as obtained by Feature Detection (see :doc:`feature_detection_overview`) but with one additional column: