DISTINGUISHING LAND USE TYPES USING SURFACE ALBEDO AND NORMALIZED DIFFERENCE VEGETATION INDEX DERIVED FROM THE SEBAL MODEL FOR THE ATANKWIDI AND AFRAM SUB- CATCHMENTS IN GHANA

Distinguishing land use types is mostly done through field surveys which does not easily capture the spatial changes in the land use/cover types. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) model was used to estimate surface albedo and NDVI, for different land use/cover types for two sub-catchments (i.e., Atankwidi and Afram) in the Volta Basin of Ghana. The mean coefficient of variation (CV) for individual land use/cover types compared to the mean CV for a given site was then used to distinguish among the land use/cover types. It was found that these parameters derived from the SEBAL model can be used to distinguish among different land use/cover types in the two subcatchments. SEBAL estimates for surface albedo and NDVI across the different land use/cover types varied from 0.05 to 0.22 and -0.41 to 0.38, respectively. The range of CVs for surface albedo and NDVI, were 5-22% and 7-175%, respectively across the different land use/cover types for the two catchments. The results of this study demonstrate that SEBAL’s derived surface albedo and NDVI can be used to distinguish land use/cover types in catchments similar to those of the study areas with few ground measurements.