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Evaluating Lightning-Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain.
Rodríguez-Pérez, José Ramón; Ordóñez, Celestino; Roca-Pardiñas, Javier; Vecín-Arias, Daniel; Castedo-Dorado, Fernando.
Afiliación
  • Rodríguez-Pérez JR; GEOINCA Research Group, Universidad de León, Ponferrada, León, Spain.
  • Ordóñez C; Department of Mining Exploitation and Prospecting, Polytechnic School of Mieres, Universidad de Oviedo, Mieres, Asturias, Spain.
  • Roca-Pardiñas J; Department of Statistics and Operations Research, SIDOR Research Group, Universidad de Vigo, Vigo, Pontevedra, Spain.
  • Vecín-Arias D; GEOINCA Research Group, Universidad de León, Ponferrada, León, Spain.
  • Castedo-Dorado F; GEOINCA Research Group, Universidad de León, Ponferrada, León, Spain.
Risk Anal ; 40(7): 1418-1437, 2020 07.
Article en En | MEDLINE | ID: mdl-32347573
It is widely accepted that the relationship between lightning wildfire occurrence and its influencing factors vary depending on the spatial scale of analysis, making the development of models at the regional scale advisable. In this study, we analyze the effects of different biophysical variables and lightning characteristics on lightning-caused forest wildfires in Castilla y León region (Central Spain). The presence/absence of at least one lightning-caused fire in any 4 × 4-km grid cell was used as a dependent variable and vegetation type and structure, terrain, climate, and lightning characteristics were used as possible covariates. Five prediction methods were compared: a generalized linear model (GLM), a random forest model (RFM), a generalized additive model (GAM), a GAM that includes a spatial trend function (GAMs) and a spatial autoregressive model (AUREG). A GAMs with just one covariate, apart from longitude and latitude for each observation included as a combined effect, was considered the most appropriate model in terms of both predictive ability and simplicity. According to our results, the probability of a forest being affected by a lightning-caused fire is positively and nonlinearly associated with the percentage of coniferous woodlands in the landscape, suggesting that occurrence is more closely associated with vegetation type than with topography, climate, or lightning characteristics. The selected GAMs is intended to inform the Regional Government of Castilla y León (the fire and fuel agency in the region) regarding identification of areas at greatest risk so it can design long-term forest fuel and fire management strategies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Incendios Forestales / Relámpago Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Risk Anal Año: 2020 Tipo del documento: Article País de afiliación: España Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Incendios Forestales / Relámpago Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Risk Anal Año: 2020 Tipo del documento: Article País de afiliación: España Pais de publicación: Estados Unidos