ngei-civil-pv/Laikipia-Solar-Suitability-MCA

GIS-based solar farm suitability analysis for Laikipia County, Kenya using Multi-Criteria Decision Analysis (MCDA) and Weighted Overlay in QGIS. # Solar PV Suitability Mapping for Laikipia County, Kenya **Multi-Criteria Analysis (MCA) using GIS and Analytical Hierarchy Process (AHP) in QGIS** ## Project Overview This repository contains a GIS-based Multi-Criteria Decision Analysis (MCDA) workflow for identifying suitable sites for Solar Photovoltaic (PV) power plants (off-grids, utility plants) in **Laikipia County, Kenya**. Laikipia County, located in the Rift Valley region of central Kenya, covers approximately 9,500 km². It features diverse landscapes ranging from semi-arid rangelands to highland areas. With abundant solar resources (high sunshine hours typical of equatorial regions), the county has strong potential for renewable energy development to support local industries (e.g., dairy processing), off-grid communities, and contribution to Kenya’s national targets for renewable energy expansion. The project applies a rigorous **GIS-MCA-AHP** approach, consistent with best practices to produce a high-resolution solar suitability map. ## Objectives - Identify and rank areas most suitable for utility-scale and mini grids solar PV development. - Exclude environmentally and technically unsuitable zones (hard constraints). - Integrate environmental, topographic, climatic, and infrastructural factors using weighting (AHP). - Provide reproducible, open workflows and data for policymakers, investors, and researchers. - Support Laikipia County’s sustainable energy planning and green growth initiatives. ## Methodology The analysis follows a standard **Multi-Criteria Evaluation (MCE)** framework in QGIS: ### 1. Project Setup & Study Area - QGIS project configured with projected CRS (EPSG:32737 – UTM Zone 37S). - Laikipia County administrative boundary used as the study area mask. - All data clipped and aligned to the boundary. ### 2. Data Collection & Preparation - **Primary Data Sources**: - Administrative boundary: Kenya National Bureau of Statistics. - Digital Elevation Model (DEM): SRTM 30m. - …