@article{article_1754579, title={A GIS and Drone-Based Risk Assessment Framework for Hydroelectric and Solar Energy Infrastructure in Disaster-Prone Areas with High Forestry and Agricultural Activity}, journal={The Eurasia Proceedings of Science Technology Engineering and Mathematics}, volume={34}, pages={268–277}, year={2025}, DOI={10.55549/epstem.1754579}, author={Alkan, Oyku and Alkan, Mehmet Nurullah}, keywords={Drones, Overlay analysis, Renewable energy risk assessment, Geospatial hazard modeling}, abstract={The increasing global demand for renewable energy has accelerated the expansion of hydroelectric
(HEPPs) and solar power plants (SEPs), frequently located in ecologically fragile and geologically hazardous
areas. This study proposes an integrated geospatial risk assessment framework combining Geographic
Information Systems (GIS) and Unmanned Aerial Vehicles (UAVs) to evaluate and mitigate multi-hazard risks
affecting renewable energy infrastructure. Focusing on Turkey’s North-Middle Black Sea Region intersected by
the seismically active North Anatolian Fault (NAF) and encompassing the geologically complex Obruk Dam
basin this research addresses an area with dense renewable energy installations and high susceptibility to
tectonic and climate-induced hazards. High-resolution UAV imagery, coupled with 3D terrain modeling, was
utilized to assess infrastructure vulnerabilities. GIS-based spatial overlay techniques integrated multiple data
layers, including active fault lines, slope instability, flood-prone zones, and land use classifications. Time-series
change detection analyses were conducted to monitor landscape dynamics related to erosion, vegetation loss,
and anthropogenic disturbances. A key component of the framework involves applying geomatics engineering
principles, such as UAV-derived digital elevation model (DEM) validation and spatial dataset calibration.Using
multi-criteria decision analysis (MCDA), critical risk hotspots particularly in the Obruk Dam basin were
identified, highlighting infrastructure segments with heightened exposure to seismic and hydrological threats.
Associated risks in surrounding agricultural and forested zones, such as wildfire vulnerability and soil
deterioration, were further assessed. This study advances geomatics engineering by presenting a scalable, UAVGIS-integrated methodology for multi-dimensional risk modeling in renewable energy planning. The proposed
framework provides a robust tool for risk-informed energy deployment while strengthening environmental
resilience in disaster-prone regions.}, publisher={ISRES Publishing}