Delineation of Cocoa Agroforests Using Multi-Season Sentinel-1 SAR Images versus RapidEye multi-spectral image
2019
Numbisi, Frederick N. | Van Coillie, Frieke M.B. | De Wulf, Robert
The data is based on field inventory from 2015 to 2017 to map cocoa agroforests and other vegetation and non-vegetation land cover. The dataset consists of geospatial data (shapefiles) of the land cover and land use in the study landscape in Bokito - within the forest-savannah transition zone of Centre Cameroon. The main aim of the study was to discriminate cocoa agroforest from transition forest; we compare the performance of texture-based classification of SAR (Synthetic Aperture Radar) images of Sentinel-1 with the result of "business as usual" multi-spectral optical image classification using a RapidEye image mosaic for the study landscape.
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