A GIS and Drone-Based Risk Assessment Framework for Hydroelectric and Solar Energy Infrastructure in Disaster-Prone Areas with High Forestry and Agricultural Activity

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 hazardousareas. This study proposes an integrated geospatial risk assessment framework combining GeographicInformation Systems (GIS) and Unmanned Aerial Vehicles (UAVs) to evaluate and mitigate multi-hazard risksaffecting renewable energy infrastructure. Focusing on Turkey's North-Middle Black Sea Region intersected bythe seismically active North Anatolian Fault (NAF) and encompassing the geologically complex Obruk Dambasin this research addresses an area with dense renewable energy installations and high susceptibility totectonic and climate-induced hazards. High-resolution UAV imagery, coupled with 3D terrain modeling, wasutilized to assess infrastructure vulnerabilities. GIS-based spatial overlay techniques integrated multiple datalayers, including active fault lines, slope instability, flood-prone zones, and land use classifications. Time-serieschange 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 engineeringprinciples, such as UAV-derived digital elevation model (DEM) validation and spatial dataset calibration.Usingmulti-criteria decision analysis (MCDA), critical risk hotspots particularly in the Obruk Dam basin wereidentified, highlighting infrastructure segments with heightened exposure to seismic and hydrological threats.Associated risks in surrounding agricultural and forested zones, such as wildfire vulnerability and soildeterioration, 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 proposedframework provides a robust tool for risk-informed energy deployment while strengthening environmentalresilience in disaster-prone regions.