Logistic regression models for human-caused wildfire risk estimation: analysing the effect of the spatial accuracy in fire occurrence data
| Autor: | F. Javier Martínez Vega, Lara Vilar del Hoyo, M. Pilar Martín Isabel |
|---|---|
| Přispěvatelé: | Ministerio de Educación y Ciencia (España), Martín, M. Pilar [0000-0002-5563-8461], Martínez Vega, Javier [0000-0002-8519-120X], Vilar del Hoyo, Lara [0000-0003-0872-1235], Martín, M. Pilar, Martínez Vega, Javier, Vilar del Hoyo, Lara |
| Rok vydání: | 2011 |
| Předmět: |
Wildland-urban interface
010504 meteorology & atmospheric sciences Kernel density estimation Euro-Mediterranean Plant Science Socio-economic Logistic regression 01 natural sciences Fire ignition points law.invention law Statistics Wildland–urban interface 0105 earth and related environmental sciences 040101 forestry Estimation Forestry 04 agricultural and veterinary sciences GIS Grid Ignition system Variable (computer science) Kernel interpolation 0401 agriculture forestry and fisheries Environmental science Interpolation |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname European Journal of Forest Research |
| ISSN: | 1612-4677 1612-4669 |
| DOI: | 10.1007/s10342-011-0488-2 |
| Popis: | About 90% of the wildland fires occurred in Southern Europe are caused by human activities. In spite of these figures, the human factor hardly ever appears in the definition of operational fire risk systems due to the difficulty of characterising it. This paper describes two spatially explicit models that predict the probability of fire occurrence due to human causes for their integration into a comprehensive fire risk–mapping methodology. A logistic regression technique at 1 × 1 km grid resolution has been used to obtain these models in the region of Madrid, a highly populated area in the centre of Spain. Socio-economic data were used as predictive variables to spatially represent anthropogenic factors related to fire risk. Historical fire occurrence from 2000 to 2005 was used as the response variable. In order to analyse the effects of the spatial accuracy of the response variable on the model performance (significant variables and classification accuracy), two different models were defined. In the first model, fire ignition points (x, y coordinates) were used as response variable. This model was compared with another one (Kernel model) where the response variable was the density of ignition points and was obtained through a kernel density interpolation technique from fire ignition points randomly located within a 10 × 10 km grid, which is the standard spatial reference unit established by the Spanish Ministry of Environment, Rural and Marine Affairs to report fire location in the national official statistics. Validation of both models was accomplished using an independent set of fire ignition points (years 2006–2007). For the validation, we used the area under the curve (AUC) obtained by a receiver-operating system. The first model performs slightly better with a value of AUC of 0.70 as opposed to 0.67 for the Kernel model. Wildland–urban interface was selected by both models with high relative importance. This research has been partially supported by the Firemap project CGL2004-06049-C04-01/CLI, funded by the Spanish Ministry of Education, through the FPI scholarship BES- 2005-7712 |
| Databáze: | OpenAIRE |
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