AI-Driven Drone Mapping for Disaster Response and Urban Planning Using GIS

Abstract

Recent advancements in artificial intelligence (AI) and geographic information systems (GIS) have enabled the use of drones for real-time mapping in disaster response and urban planning. This paper explores the integration of AI-driven drone technology with GIS to enhance situational awareness, optimize resource allocation, and improve decision-making during emergencies and urban development projects. By leveraging machine learning algorithms, drones can rapidly process aerial imagery, detect changes in terrain, and provide critical insights for first responders and urban planners. We discuss various AI techniques used for data analysis, the challenges in implementing AI-driven drone mapping, and potential solutions to overcome these hurdles. Additionally, case studies demonstrate the effectiveness of this approach in real-world scenarios. Our findings indicate that AI-driven drones equipped with GIS capabilities significantly improve disaster response times and urban planning accuracy, ultimately leading to more resilient and sustainable communities.