Integrating Geo-localized Smartphone Photos and Drone Imagery to Validate Optimum Gas Pipeline Routes in West Africa, Senegal

In this study, we utilized UAV imagery and geo-localized photos taken from multiple directions (north, south, east, and west) to comprehensively characterize elements of interest. These elements include the proposed locations of future routes or houses, ground elevation, and the accessibility of areas along a proposed pipeline route. Our aim was to validate the selection of optimal gas pipeline routes, including shore crossings and control valve stations, determined through the Analytical Hierarchical Process (AHP) in the Sangomar perimeter, West Africa, Senegal. The methodology comprised two parts: first, an AHP-based multi-criteria analysis (MCA) to select optimal pipeline routes; second, a ground verification process using UAV and geo-localized photos. The AHP approach considered 16 criteria, including future land-use information, to identify one optimal route (OPR) and two alternatives (APR1 and APR2). Ground verification involved a physical inspection of strategic points along each route, capturing detailed drone or smartphone imageries to validate the AHP model's accuracy. Our findings revealed that while the (OPR) was initially deemed optimal based on AHP modeling, ground verification suggested that (APR2) might be more suitable due to fewer negative impacts on surrounding elements. This integrated approach of AHP modeling and UAV-based ground verification demonstrates a robust framework for pipeline route selection, enhancing both the accuracy and practicality of the proposed routes. The study highlights the significant potential of combining AHP modeling with advanced imaging technologies for effective infrastructure planning. Future research should explore additional methodologies to support and confirm our findings, emphasizing the importance of involving local authorities and communities in the route selection process. This inclusive approach ensures that the selected routes are technically optimal and socially acceptable, aligning with both technical and community needs.