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Modeling spatio-temporal wildfire ignition point patterns
Authors:Amanda S Hering  Cynthia L Bell  Marc G Genton
Institution:(1) Department of Statistics, Texas A&M University, College Station, TX 77843-3143, USA;(2) Department of Econometrics, University of Geneva, Bd du Pont-d’Arve 40, 1211 Geneva 4, Switzerland
Abstract:We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-function and argue that clustering is less important than initially thought. We also use K-cross functions to study multitype point patterns, both under homogeneity and inhomogeneity assumptions, and reach similar conclusions as above regarding the amount of clustering. Of particular interest is our finding that prescribed burns seem not to reduce significantly the occurrence of wildfires in the current or subsequent year over this large geographical region. Finally, we describe various point pattern models for the location of wildfires and investigate their adequacy by means of recent residual diagnostics.
Contact Information Marc G. Genton (Corresponding author)Email: Email:
Keywords:Clustering  Diagnostics  Inhomogeneous            K-function  Marked  Multitype  Point process  Residuals
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