A rangeland management-oriented approach to map dry savanna − Woodland mosaics

Tropical savannas have a patchy vegetation structure and heterogeneous composition that complicates their mapping and management. Land managers need detailed vegetation information, especially as tropical savannas often support extensive ranching systems or wildlife-based tourism and face specific challenges such as bush thickening, drought, bushfires and, in Africa, browsing by large game. Since existing methods to map savanna vegetation mosaics rarely provide the resolution or speed required, this study aimed to characterise savanna vegetation with sufficient detail for management purposes and sufficient generalisation for the assessment of processes at a landscape level, using an easy, quick, and cost-efficient system. The study area is a semi-arid savanna in a small game reserve south of Etosha National Park in Namibia. A rapid field assessment focused on the woody vegetation and used the Bitterlich method. Indicator species analysis and MRPP tests resulted in five mixed woody vegetation classes. Random Forest was used to model vegetation composition, structure and woody cover. The highest accuracy was obtained for vegetation composition (77 %) and the lowest for vegetation cover (71 %) with similar accuracies at a resolution of 10 m compared to 30 m. The most important predictors were a radar mosaic (ALOS PALSAR HV) and Sentinel-2 data representing days in wet and dry seasons, with MSAVI₂ a more suitable vegetation index than NDVI. Other predictors such as land surface temperature during winter nights, geology, and distance to water points contributed to the models. The final vegetation map contains 10 classes based on woody vegetation composition and structure. The most dominant classes were Colophospermum mopane – Terminalia prunioides woodland (33 %) and bushland (18 %) with grassland only covering 2.5 %. The method described here was driven by management requirements and can be used for bush control monitoring, quantifying the carbon pool and carrying capacity. It combines an old field survey method with free state-of-the-art datasets and algorithms. The focus on woody vegetation minimises the dependence on the intermittent presence of grasses and herbs in semi-arid savannas.