Bayode001/Nigeria_Renewable_Suitability

Mapping Renewable Energy Potential in Nigeria Using GIS Nigeria Renewable Energy GIS Suitability Project Solar • Wind • Hydro | QGIS + Python + GDAL Workflow This repository contains a complete GIS-based suitability analysis workflow for renewable energy development in Nigeria. The project integrates solar, wind, and hydro suitability using QGIS, GDAL, raster processing, multi-criteria decision analysis (MCDA), and geospatial modelling. 🔍 Project Purpose This repository provides a spatial decision-support system to inform renewable energy planning, investment prioritization, and policy formulation in Nigeria. To create spatially accurate, data-driven suitability maps for supporting renewable energy planning in Nigeria. The project outputs: GIS-ready analytical outputs suitable for feasibility screening, strategic energy planning, and donor-funded infrastructure programmes. 🌞 Solar Suitability Map 🌬️ Wind Suitability Map 💧 Hydro Suitability Map ⚡ Combined Renewable Energy Suitability Index 📍 Candidate Sites / Priority Zones 🗂️ Datasets Used Raster Data Digital Elevation Model (DEM) Landcover (ESA WorldCover / Copernicus) Global Horizontal Irradiance (GHI) Wind Speed (ERA5 / Global Wind Atlas) Hydro layers (flow accumulation, slope, rivers) Roads & grid network Vector Data State boundaries (GADM, OCHA) Hydrology (rivers, catchments) Transmission lines & substations ⚙️ Processing Workflow The GIS workflow includes: 1. Data Acquisition Download raw datasets into data_raw/. 2. Preprocessing Reproject all rasters to WGS84 / UTM Clip to Nigeria AOI Resample layers to common resolution Convert vector → raster where needed Build landmask All spatial analysis was conducted in WGS 84 / UTM Zone 32N (EPSG:32632). 3. Criteria Computation Solar: GHI reclassification Slope constraints Land cover restrictions Wind: Wind speed at 100m Roughness / surface friction Distance to grid Hydro: Flow accumulation Stream network extraction Head & slope constraints 4. Multi-Criteria Decision A …