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Classification of rare land cover types : Distinguishing annual and perennial crops in an agricultural catchment in South Korea

Bogner, Christina; Seo, Bumsuk 1; Rohner, Dorian; Reineking, Björn
1 Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Many environmental data are inherently imbalanced, with some majority land use and land cover types dominating over rare ones. In cultivated ecosystems minority classes are often the target as they might indicate a beginning land use change. Most standard classifiers perform best on a balanced distribution of classes, and fail to detect minority classes. We used the synthetic minority oversampling technique (smote) with Random Forest to classify land cover classes in a small agricultural catchment in South Korea using modis time series. This area faces a major soil erosion problem and policy measures encourage farmers to replace annual by perennial crops to mitigate this issue. Our major goal was therefore to improve the classification performance on annual and perennial crops. We compared four different classification scenarios on original imbalanced and synthetically oversampled balanced data to quantify the effect of smote on classification performance. smote substantially increased the true positive rate of all oversampled minority classes. However, the performance on minor classes remained lower than on the majority class. We attribute this result to a class overlap already present in the original data set that is not resolved by smote. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000080149
Veröffentlicht am 19.02.2018
DOI: 10.1371/journal.pone.0190476
Zitationen: 16
Web of Science
Zitationen: 14
Zitationen: 17
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 1932-6203
KITopen-ID: 1000080149
HGF-Programm 12.02.02 (POF III, LK 01) Vegetation climate- and land use system
Erschienen in PLoS one
Verlag Public Library of Science (PLoS)
Band 13
Heft 1
Seiten Art.Nr. e0190476
Schlagwörter Land use, Land cover, Remote sensing, Crop classification, Complex agricultural terrain
Nachgewiesen in Dimensions
Web of Science
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