Optimizing Site Selection Under Extreme Weather Conditions Based on Multi-Layered Raster Overlay Technology

Abstract

With the increasing likelihood of more severe weather and natural disasters due to climate change, extreme weather events are becoming a crisis for property owners and insurance companies. The Resilient Property Assessment Model (RPE) is established based on geostatistical kriging techniques to evaluate property locations under extreme weather conditions in the United States, aiding decision-making for real estate and insurance industries. Initially, discrete meteorological data is extrapolated into continuous fields, forming the optimization model. Subsequently, it integrates GIS’s multi-layered raster overlay technology to precisely identify prime areas for property development and insurance coverage through comprehensive assessments of 13 natural and social factors. Findings reveal that 8 states possess high-quality insurance markets, primarily concentrated in the eastern and central border regions of the United States. Additionally, leveraging existing data, it investigates the spatial dynamics of North Atlantic tropical cyclones, tracking them to enhance regional insurance strategies, further affirming the reliability of the RPE model. This paper aims to provide corresponding recommendations for local real estate site selection and insurance model adjustments through the RPE model, to better cope with the crisis of frequent extreme weather events.