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| Titel |
Hydrometeor classification from two-dimensional video disdrometer data |
| VerfasserIn |
J. Grazioli, D. Tuia, S. Monhart, M. Schneebeli, T. Raupach, A. Berne |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 7, no. 9 ; Nr. 7, no. 9 (2014-09-09), S.2869-2882 |
| Datensatznummer |
250115892
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| Publikation (Nr.) |
 copernicus.org/amt-7-2869-2014.pdf |
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| Zusammenfassung |
| The first hydrometeor classification technique based on
two-dimensional video disdrometer (2DVD) data is presented. The method provides
an estimate of the dominant hydrometeor type falling over time
intervals of 60 s during precipitation, using the
statistical behavior of a set of particle descriptors as input, calculated
for each particle image. The employed supervised algorithm is
a support vector machine (SVM), trained over 60 s precipitation time steps labeled by visual inspection. In this way, eight dominant
hydrometeor classes can be discriminated. The algorithm achieved high classification performances, with median overall accuracies
(Cohen's K) of 90% (0.88), and with accuracies
higher than 84% for each hydrometeor class. |
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