Application of Remote Sensing for Drought Monitoring and Management in the Lake Chad Basin, Borno State

Drought monitoring in the Lake Chad Basin demands operationally practical tools that function under conditions of limited ground station infrastructure. This study examines the application of remote sensing products for professional drought monitoring and management support within the Nigerian portion of the Lake Chad Basin. MODIS-derived Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and Land Surface Temperature (LST) data from 2018 to 2023 were analyzed in conjunction with CHIRPS rainfall estimates to generate composite drought severity maps at monthly time steps. Validation against NiMet station data and structured interviews with Borno State Emergency Management Agency (SEMA) staff assessed the operational utility of the approach. Results demonstrate that VCI-based drought severity maps correctly identified all four drought episodes documented by SEMA over the study period, with a spatial accuracy of 82 percent at district level. The operational drought monitoring workflow, implemented in open-source QGIS software, was evaluated by 15 SEMA technical staff as practically usable within existing institutional capacity constraints. Key management applications identified include early warning triggers for food security response pre-positioning and targeted livestock movement advisory. Recommendations include institutionalization of the remote sensing monitoring workflow within SEMA's early warning system and monthly data sharing protocols with NiMet Maiduguri. Keywords: remote sensing, drought monitoring, Lake Chad Basin, VCI, early warning.