Can the adjoining councils influence the wildfire patterns? The role of spatial heterogeneity to assess the public forest policy against fires
Wildfires are an increasing threat, particularly in Galicia (NW Spain), with often significant economic and environmental impacts on landowners and ecosystems. Therefore, public policies should aim to reduce the risk and impacts of wildfires, which requires general frameworks and adequate tools to s...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:minerva_____::aa15658d47d98e9050de1ee701042c3c |
| Acceso en línea: | https://hdl.handle.net/10347/46570 |
| Access Level: | acceso abierto |
| Palabra clave: | Affected area Fire extension Spatial panel data analysis Spatial statistics Suppression time Wildfires |
| Sumario: | Wildfires are an increasing threat, particularly in Galicia (NW Spain), with often significant economic and environmental impacts on landowners and ecosystems. Therefore, public policies should aim to reduce the risk and impacts of wildfires, which requires general frameworks and adequate tools to support policy decisions. Given the spatial and temporal heterogeneity of wildfires at the local scale, such support tools should take these dimensions into account. This study aims to analyse the spatial relations between wildfire patterns at the municipal level and model the percentage of affected areas considering both wildfire-related variables and their spatial dependencies. To achieve this, spatial pattern analysis was applied on the percentage of total, forested and non-forested area affected by wildfires, and three wildfire-related variables (Wildfire density, Fire extension and Suppression time) on each of the 313 individual Galician municipalities per season during the 1991–2019 period. To analyse global and local spatial autocorrelation, Moran’s I and LISA statistics were calculated to define the most adequate contiguity matrix. The detected spatial relations between neighbouring municipalities were integrated into an econometric panel data analysis, which generated spatial econometric models with the percentage of total, forested and non-forested area affected by wildfires as dependent variables, while testing for significance the three wildfire-related variables. Spatial pattern analysis showed higher susceptibility for wildfire impacts in southern municipalities. Spatial autocorrelation was higher for contiguous municipalities across all variables. The econometric models suggest a positive effect of developing coordinated actions against wildfires that could reduce wildfire impact between neighbouring councils. |
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