Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa

Remote Sensing

Gerald Forkuor¹  Christopher Conrad¹  Michael Thiel¹  Tobias Ullmann² 

[1] Department of Remote Sensing, University of Wurezburg, Oswald-Külpe-Weg 86, 97074 Wuerzburg, Germany; E-Mails:;Institute for Geography and Geology, University of Wuerzburg, 97074 Am Hubland, Germany; E-Mail:

关键词: crop mapping;    agriculture;    West Africa;    RapidEye;    TerraSAR-X;    random forest;   

DOI  :  10.3390/rs6076472

来源: mdpi

【 摘 要 】

Crop mapping in West Africa is challenging, due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. To address this challenge, we integrated high spatial resolution multi-temporal optical (RapidEye) and dual polarized (VV/VH) SAR (TerraSAR-X) data to map crops and crop groups in northwestern Benin using the random forest classification algorithm. The overall goal was to ascertain the contribution of the SAR data to crop mapping in the region. A per-pixel classification result was overlaid with vector field boundaries derived from image segmentation, and a crop type was determined for each field based on the modal class within the field. A per-field accuracy assessment was conducted by comparing the final classification result with reference data derived from a field campaign. Results indicate that the integration of RapidEye and TerraSAR-X data improved classification accuracy by 10%–15% over the use of RapidEye only. The VV polarization was found to better discriminate crop types than the VH polarization. The research has shown that if optical and SAR data are available for the whole cropping season, classification accuracies of up to 75% are achievable.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland