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Analyzing wildfire evacuation behavior with GPS data

With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This study proposes a new methodology to analyze human behavior during wildfires by leveraging a large-scale GPS dataset. This methodology includes a home-location inference algorithm and an evacuation-behavior inference algorithm, to systematically identify different groups of wildfire evacuees (i.e., self-evacuee, shadow evacuee, evacuee under warning, and ordered evacuee).

Key words: wildfire, GPS data, evacuation, human behavior

Zhao, X., Xu, Y., Lovreglio, R., Kuligowski, E., Nilsson, D., Cova, T., Wu, A., Yan, X., Cao, Z. Estimating wildfire evacuation decision and departure timing using large-scale GPS data. [Download Preprint].