Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland
Abstract Prosopis spp. is a fast and aggressive invader threatening many arid and semi arid areas globally. The species is native to the American dry zones and was introduced in Somaliland for dune stabilization and fuel wood production in the 1970s and 1980s. Its deep rooting system is capable of tapping into the groundwater table thereby reducing its reliance on infrequent rainfalls and near surface water. The competitive advantage of Prosopis is further fuelled by the hybridization of the many introduced subspecies that made the plant capable of adapting to the new environment and replacing endemic species. This study aimed to test the mapping accuracy achievable with Landsat 8 data acquired during the wet and the dry seasons within a Random Forest (RF) classifier, using both pixel and object based approaches. Maps are produced for the Hargeisa area (Somaliland) where reference data was collected during the dry season of 2015. Results were assessed through a 10 fold cross validation procedure. In our study, the highest overall accuracy (74% was achieved when applying a pixel based classification using a combination of the wet and dry season Earth observation data. Object based mapping were less reliable due to the limitations in spatial resolution of the Landsat data (1530 m) and problems in finding an appropriate segmentation scale.
Int. J. Appl. Earth Obs. Geoinformation