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Classification of wildfires in relation to land cover types and associated variables by applying cluster analysis: a case study in the Iberian Peninsula

Classification of wildfires in relation to land cover types and associated variables by applying cluster analysis: a case study in the Iberian Peninsula
Classification of wildfires in relation to land cover types and associated variables by applying cluster analysis: a case study in the Iberian Peninsula

Wildfires are a major environmental problem that have both economic and ecological impacts. Wildfires typically spread in a particular pattern, determined by factors such as the elements on the ground that catch fire or their geographic location. This study reports and discusses how wildfires in the Valencian Community, Spain, have been spatially grouped in recent years (from 2016 to 2020). It also characterizes each cluster in terms of location and land cover. An exploratory analysis of the environmental variables associated with wildfires has been conducted using finite Gaussian mixture models in R (R package mclust). The primary findings can be used to better understand the types of wildfires that occur in individual spatial zones. Some interesting cluster patterns in specific geographical areas, such as river basins, have also been reported. The method can identify clusters of fires by detecting areas with similar characteristics at the land use level. It also allows for the implementation of measures aimed at reducing the impacts of wildfires and can help in the extinction of wildfires based on the characteristics of all the fires grouped using spatial and land cover dimensions.

Environmental covariates, Geographic clustering, Mclust, Mixed-methods, Wildfire patterns
0167-6369
Serra, Laura
95c48bad-cb5f-4364-b70c-9d27c5aeb6e5
Juan, Pablo
f3648398-5752-4dd0-9410-835566b659f4
Díaz-Avalos, Carlos
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Aragó, Pau
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Chaudhuri, Somnath
ae0507e0-f920-4438-bc9f-ecdd5ac8967a
Trilles, Sergio
a4e6a50c-80c4-464f-b4d2-7399ec72e095
Serra, Laura
95c48bad-cb5f-4364-b70c-9d27c5aeb6e5
Juan, Pablo
f3648398-5752-4dd0-9410-835566b659f4
Díaz-Avalos, Carlos
c3d206d1-9a32-4e8c-88ab-0b7f2cb18e30
Aragó, Pau
2b8717bb-393e-4951-8185-4dc9a7796489
Chaudhuri, Somnath
ae0507e0-f920-4438-bc9f-ecdd5ac8967a
Trilles, Sergio
a4e6a50c-80c4-464f-b4d2-7399ec72e095

Serra, Laura, Juan, Pablo, Díaz-Avalos, Carlos, Aragó, Pau, Chaudhuri, Somnath and Trilles, Sergio (2025) Classification of wildfires in relation to land cover types and associated variables by applying cluster analysis: a case study in the Iberian Peninsula. Environmental Monitoring and Assessment, 197 (6), [619]. (doi:10.1007/s10661-025-14053-y).

Record type: Article

Abstract

Wildfires are a major environmental problem that have both economic and ecological impacts. Wildfires typically spread in a particular pattern, determined by factors such as the elements on the ground that catch fire or their geographic location. This study reports and discusses how wildfires in the Valencian Community, Spain, have been spatially grouped in recent years (from 2016 to 2020). It also characterizes each cluster in terms of location and land cover. An exploratory analysis of the environmental variables associated with wildfires has been conducted using finite Gaussian mixture models in R (R package mclust). The primary findings can be used to better understand the types of wildfires that occur in individual spatial zones. Some interesting cluster patterns in specific geographical areas, such as river basins, have also been reported. The method can identify clusters of fires by detecting areas with similar characteristics at the land use level. It also allows for the implementation of measures aimed at reducing the impacts of wildfires and can help in the extinction of wildfires based on the characteristics of all the fires grouped using spatial and land cover dimensions.

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s10661-025-14053-y - Version of Record
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Accepted/In Press date: 15 April 2025
e-pub ahead of print date: 3 May 2025
Published date: 3 May 2025
Keywords: Environmental covariates, Geographic clustering, Mclust, Mixed-methods, Wildfire patterns

Identifiers

Local EPrints ID: 503125
URI: http://eprints.soton.ac.uk/id/eprint/503125
ISSN: 0167-6369
PURE UUID: c2ba961e-decf-43e4-8090-cc37ed1e9d1d
ORCID for Somnath Chaudhuri: ORCID iD orcid.org/0000-0003-4899-1870

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Date deposited: 22 Jul 2025 16:35
Last modified: 22 Aug 2025 02:43

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Contributors

Author: Laura Serra
Author: Pablo Juan
Author: Carlos Díaz-Avalos
Author: Pau Aragó
Author: Somnath Chaudhuri ORCID iD
Author: Sergio Trilles

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