Non-parametric comparative analysis of the spatiotemporal pattern of human-caused and natural wildfires in Galicia
M. F. Marey-Pérez
A * , Isabel Fuentes-Santos B , Paula Saavera-Nieves C and Wenceslao González-Manteiga C
+ Author Affiliations
- Author Affiliations
A PROePLA Research Group, Department of Crop Production and Engineering Projects, Universidade de Santiago de Compostela, Spain.
B Marine Research Institute, Spanish National Research Council, Spain.
C Department of Statistics, Mathematical Analysis and Optimisation, University of Santiago de Compostela, Spain.
* Correspondence to: manuel.marey@usc.es
International Journal of Wildland Fire 32(2) 178-194 https://doi.org/10.1071/WF22030
Submitted: 15 March 2022 Accepted: 22 November 2022 Published: 23 December 2022
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF.
Abstract
Background: Wildfire is a major environmental threat worldwide and climate change is expected to increase its severity. Galicia has suffered high wildfire incidence during the last decades, most wildfires being from arson, in contrast with the low rate of natural wildfires.
Aim: This work aims to characterise the spatiotemporal dynamics of human-caused and natural fires in Galicia.
Methods: We apply first- and second-order non-parametric inference to spatiotemporal wildfire point patterns.
Key results: The distribution of natural wildfires remained stable over years, with high incidence in summer and in the eastern area of Galicia. Arson wildfires had aggregated patterns, with strong interaction between outbreaks and fires, and their distribution varied both over and within years, with high incidence shifting between the southern and western areas, and high hazard in early spring and late summer. Negligence wildfire patterns showed short-distance aggregation, but large-distance aggregation between outbreaks and fires; their spatial distribution also varied between and within years.
Conclusions: Different models and covariates are required to predict the hazard from each wildfire type. Natural fires are linked to meteorological and environmental factors, whereas socioeconomic covariates are crucial in human-caused wildfires.
Implications: These results are the basis for the future development of predictive spatiotemporal point process models for human-caused wildfires.
Keywords: inhomogeneous point processes, intensity function, non-parametric inference, smooth bootstrap, Spain wildfire, spatiotemporal interactions, wildfire hazard.
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