An Integrated GIS and AHP based Approach for Drone Optimized Large Scale Flood Imaging

Abstract

A novel framework was introduced to integrate drone technology with flood risk mapping and was named Drone Optimized Flood Risk Map (DOFRM), it uses a GIS-based Multi-Criteria Decision Model (MCDM), Analytical Hierarchy Process (AHP) and drone optimized grid. After reviewing specifications of 178 contemporary drones, a grid size of 1.2x1.2 km was determined to be optimal for drone surveys. This grid was overlaid onto a flood risk map derived from multiple hazards and vulnerabilities, selected based on an in-depth literature review. Weights for these factors were determined using AHP, and the study area was District Rajanpur, Pakistan. Stakeholders, including emergency responders, drone operators, and GIS specialists, evaluated this map using the TAM survey method. This approach identified 17% of the study area as highly susceptible to flooding. Highly susceptible area was further subdivided based on critical features including urban areas (3%), active channel (5%), roads (6%), rail networks (1%) stream networks (3%) and all populated areas (9%) for smart drone employment in large scale floods. The method allows for further subdivision of critical features based on grid size and available drone effort for various survey objectives. This approach can be applied by disaster response organizations for incorporating drones into disaster mitigation planning and large-scale flood survey, marking a new paradigm in flood mitigation strategies.