Land is an essential natural resource. However, with anthropogenic activities on the savanna landscape being scattered resulting in landscape degradation. It has become imperative to monitor these variable disturbances for a complete understanding of their impact on the savanna landscape. With increasing demands to keep abreast with changing Land Use Land Cover (LULC) in savanna landscapes, therefore, there is the need to model an approach to accurately take inventory of savanna landscapes as a whole for easy and quick understanding of changing trends in vegetation cover.
Our researcher, Kenneth Aidoo’s article on “Assessment of multi-sensor approach to savanna landscape mapping in Ghana” focuses on combining optical and radar data in land cover mapping, using Random Forest and Support Vector Machine in Google Earth Engine (GEE) and examined the accuracies of LULC maps, produced by combined optical sensors alone and both optical and radar sensors.
