Imperial College London
Alternate

ProfessorMartaBlangiardo

Faculty of Medicine, School of Public Health

Chair in Biostatistics
 
 
 
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Contact

 

m.blangiardo Website

 
 
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Location

 

705School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{de:2024:10.1007/s13253-024-00617-x,
author = {de, Rivera ÓR and Espinosa, J and Madrigal, J and Blangiardo, M and López-Quílez, A},
doi = {10.1007/s13253-024-00617-x},
journal = {Journal of Agricultural, Biological and Environmental Statistics},
title = {Spatio-temporal marked point process model to understand forest fires in the Mediterranean basin},
url = {http://dx.doi.org/10.1007/s13253-024-00617-x},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Understanding and predicting forest fires have proved a highly difficult endeavour, which requires extending and adapting complex models used in different fields. Here, we apply a marked point process approach, commonly used in ecology, which uses multiple Gaussian random fields to represent dynamics of Mediterranean forest fires in a spatio-temporal distribution model. Inference is carried out using Integrated Nested Laplace Approximation (INLA) with inlabru, an accessible and computationally efficient approach for Bayesian hierarchical modelling, which is not yet widely used in species distribution models. Using the marked point process approach, intensity of forest fires and dispersion were predicted using socioeconomic factors and environmental and fire-related variables. This demonstrates the advantage of complex model components in accounting for spatio-temporal dynamics that are not explained by environmental variables. Introduction of spatio-temporal marked point process can provide a more realistic perspective of a system, which is of particular importance for a practical and impact-focused worldwide problem such as forest fires.
AU  - de,Rivera ÓR
AU  - Espinosa,J
AU  - Madrigal,J
AU  - Blangiardo,M
AU  - López-Quílez,A
DO  - 10.1007/s13253-024-00617-x
PY  - 2024///
SN  - 1085-7117
TI  - Spatio-temporal marked point process model to understand forest fires in the Mediterranean basin
T2  - Journal of Agricultural, Biological and Environmental Statistics
UR  - http://dx.doi.org/10.1007/s13253-024-00617-x
UR  - http://hdl.handle.net/10044/1/111078
ER  -
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