The use of remote sensing to monitor and estimate the rate of savanna degradation is becoming an increasingly high priority for rangeland researchers across Sub-Saharan Africa. Over the past three decades, remote sensing, geographic information system (GIS), and landscape ecology methods have been gradually integrated to estimate degradation inÂ savanna grasslands. It is important to have quantitative data demonstrating the magnitude of change so that rational land use strategies can be formulated and implemented and root causes of degradation addressed. To extract mapping features, this study utilizes Landsat multispectral scenes change-detection and Google images. Landsat scenes between 1973 and 2013 were used for targeted vegetation detection with the Spectral Angle Mapper (SAM) algorithm in Exelis Visual Information Solutions (ENVI) software. Locations with the greatest loss of vegetative cover were identified and mapped as zones experiencing extreme rangeland change. These zones occur particularly above 1,500m elevation, where abundant precipitation and multiple anthropogenic agropastoral influences have significantly transformed the agrarian landscape. Camaroon's Western High Plateau is covered by â€œprairieâ€ grass savanna vegetation that constitutes very rich pasture for grazing. However, with expanding human and animal populations, land use conflicts between resident farmers and grazers have occurred due to overgrazing, expansion of invasive weeds, conversion of rangelands to farmland, and deforestation.
USING REMOTE SENSING TO MAP AND ESTIMATE DEGRADATION IN SAVANNA GRASSLANDS IN CAMEROON
Society for Range Management
SRM Sacramento, CA