Agricultural Land Use Maps at RapidEye (5m) Scale for Dano Watershed (Burkina Faso) 2012 and 2013

These LULC maps were created through automatic digital classification of RapidEye imagery acquired during the cropping season of 2012 and early dry season of 2013. Three monthly time-steps (June and October, 2012; February 2013) were analyzed.Reference (or field) data on which the classification was based were acquired through a field campaign that lasted from May to October 2012. Standard image pre-processing techniques such as geometric and radiometric correction were conducted on the data prior to classification. The Random Forest classification algorithm was used for classification. Two levels of classification were conducted: (1) a level 1 classification which includes four broad LULC classes and (2) a level 2 classification which comprises of nine LULC classes. The poor temporal coverage of the RapidEye imagery made the accurate delineation of certain crop classes (e.g. groundnuts) very challenging. Nonetheless, an overall accuracy of 70% was obtained