Spatio-temporal point process modelling of fires in Sicily exploring human and environmental factors

TL;DR

This study models the spatio-temporal distribution of wildfires in Sicily using point process theory, revealing significant influences of human activities and environmental factors on fire occurrence.

Contribution

It introduces a novel application of spatio-temporal point process models to analyze wildfire dynamics considering land use and environmental variables.

Findings

Human activities significantly affect wildfire distribution.

Environmental factors like temperature and wind influence fire timing.

Altitude and slope impact spatial fire occurrence.

Abstract

In 2023, Sicily faced an escalating issue of uncontrolled fires, necessitating a thorough investigation into their spatio-temporal dynamics. Our study addresses this concern through point process theory. Each wildfire is treated as a unique point in both space and time, allowing us to assess the influence of environmental and anthropogenic factors by fitting a spatio-temporal separable Poisson point process model, with a particular focus on the role of land usage. First, a spatial log-linear Poisson model is applied to investigate the influence of land use types on wildfire distribution, controlling for other environmental covariates. The results highlight the significant effect of human activities, altitude, and slope on spatial fire occurrence. Then, a Generalized Additive Model with Poisson-distributed response further explores the temporal dynamics of wildfire occurrences, confirming their dependence on various environmental variables, including the maximum daily temperature, wind speed, surface pressure, and total precipitation.