A Spatial Agent-Based Model for Preemptive Evacuation Decisions During Typhoon

TL;DR

This paper introduces a spatial agent-based model simulating preemptive evacuation decisions during typhoons, incorporating demographic, geospatial, and risk perception factors to improve disaster response strategies.

Contribution

It presents a novel agent-based model that integrates demographic data, geospatial information, and risk perception to simulate evacuation decisions during typhoons.

Findings

All model parameters significantly influence evacuation decisions.

Perceived risk factors are crucial in determining evacuation behavior.

The model can predict evacuation patterns based on various risk factors.

Abstract

Natural disasters continue to cause tremendous damage to human lives and properties. The Philippines, due to its geographic location, is considered a natural disaster-prone country experiencing an average of 20 tropical cyclones annually. Understanding what factors significantly affect decision making during crucial evacuation stages could help in making decisions on how to prepare for disasters, how to act appropriately and strategically respond during and after a calamity. In this work, an agent-based model for preemptive evacuation decisions during typhoon is presented. In the model, civilians are represented by households and their evacuation decisions were based from calculated perceived risk. Also, rescuer and shelter manager agents were included as facilitators during the preemptive evacuation process. National and municipal census data were employed in the model, particularly for the demographics of household agents. Further, geospatial data of a village in a typhoon-susceptible municipality was used to represent the environment. The decision to evacuate or not to evacuate depends on the agent's perceived risk which also depends on three decision factors: characteristics of the decision maker (CDM); capacity related factors (CRF); and hazard related factors (HRF). Finally, the number of households who decided to evacuate or opted to stay as influenced by the model`s decision factors were determined during simulations. Sensitivity analysis using linear regression shows that all parameters used in the model are significant in the evacuation decision of household agents.