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An Active-Passive Microwave Land Surface Classification from GPM

Citation Author(s):
Stephen Munchak (NASA GSFC)
Sarah Ringerud
Ludovic Brucker
Yalei You
Iris de Gelis
Catherine Prigent
Submitted by:
Stephen Munchak
Last updated:
DOI:
10.21227/fypd-zj65
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Research Article Link:
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Abstract

This dataset is compiled from five years of observation from the Global Precipitation Measurement (GPM) core observatory Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). Retrieved emissivites and surface backscatter cross sections are gridded at quarter-degree, monthly resolution separately for non-snow-covered land, snow-covered land, and sea ice. A Kohonen classification technique was used to cluster surfaces based on these characteristics; the monthly gridded classifications are also available in this dataset, along with the corresponding cluster centers and covariance matrices. These data are meant to supplement the IEEE TGRS publication with the same title and authors.

Instructions:

These data are stored as numpy (.npy) files. Sample reading and plotting code is provided by the Jupyter notebook.

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