Geospatial Electrocution Risk Mapping Using Satellite Data: A Google Earth Engine Framework for Public Safety in Flood-Prone Cities

This study presents a practical geospatial approach for evaluating the danger of electrical accidents in flood-affected urban areas by using the Google Earth Engine (GEE) platform. Flooded regions were identified from Sentinel-1 SAR imagery through a calibrated backscatter threshold technique, which showed about 94% accuracy when compared with validation data. To map potential electrocution hazards, the workflow brings together several datasets: SRT M elevation information, VIIRS night-light data as an indicator of population distribution, a synthetic layout of electric poles generated from OpenStreetMap, and near–real-time weather observations. A 14 × 14 pole grid (196 poles) was created and tested in two locations in Chennai—Anna Nagar and Thiruvanmiyur—to demonstrate how the model performs in real urban settings. The resulting map classifies risk into four categories: very high risk for poles that are flooded and located in populated zones; moderate risk for areas within 100 m of water accumulation; low-to-moderate risk for areas 100–200 m away; and low risk beyond 200 m. The validation process confirmed the accuracy of the flood extraction and showed that the method can effectively highlight electrical infrastructure that requires urgent attention. Overall, the framework can assist authorities in making quicker decisions about power shutdowns in vulnerable neighborhoods, helping reduce the likelihood of electrocution during major urban flood events.The GEE-driven approach ultimately provides a practical and cost-effective way to support flood-risk mitigation efforts and improve the management of urban infrastructure