Multi-Criteria Decision Analysis for Renewable Energy Site Selection in the Sahel Belt of Nigeria: A Geospatial Methodology

Renewable energy site selection in Nigeria's Sahel belt, encompassing Sokoto, Kebbi, Zamfara, and Katsina States, involves complex trade-offs between resource abundance, infrastructure accessibility, land use conflicts, community acceptance, environmental sensitivity, and grid proximity that single-criterion approaches cannot adequately resolve, motivating development of an integrated multi-criteria geospatial methodology. This study develops and applies an original multi-criteria decision analysis framework for renewable energy site selection in Nigeria's Sahel belt, integrating geospatial data processing with analytical hierarchy process weighting and sensitivity analysis to produce ranked suitability maps for solar and wind energy development. The methodological contribution is an integrated geospatial multi-criteria decision analysis protocol that systematically addresses data uncertainty, stakeholder weight heterogeneity, and spatial scale selection challenges previously unresolved in Nigerian renewable energy siting literature. Geospatial data layers including solar irradiance, wind speed, slope, land cover, proximity to transmission infrastructure, protected areas, and community settlement patterns were assembled and processed at 250-metre resolution. Analytical hierarchy process weights were elicited from 30 expert stakeholders using structured pairwise comparison surveys and aggregated using a geometric mean approach. Uncertainty analysis was conducted using Monte Carlo simulation of weight perturbations. Results identify 2.3 million hectares of high-suitability land across the Sahel belt with combined solar and wind generation potential exceeding 180 gigawatts, representing a transformative energy resource base. The suitability maps are validated against three existing project sites. Keywords: multi-criteria decision analysis, site selection, renewable energy, Sahel belt Nigeria, geospatial methodology.