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

ABSTRACT: 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

SUBMITTER: Bogner C 

PROVIDER: S-EPMC5784906 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature