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Fast-moving wildfires pose difficult modeling challenges, including accounting for heterogeneity in individual evacuee behavior and capturing a complex changing system across time dimensions. Here, we employ a NetLogo agent-based model that enables the development of behavioral models for nearest shelter evacuations using origin information. We use GIS shape files (i.e., road network, building blocks etc.) and the spatiotemporal wildfire dynamics (wind speed, direction and possibility of spread) to support our analysis. Our framework is capable of generating various wildfire scenarios that capture the overall evacuation processes. We can use the simulations to demonstrate the feasibility of agent-based models and to compare them under different fire evacuation scenarios.

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