Socioeconomic drivers data from GIS to predict forest fires at regional level: kernel density fires response variable

  1. VILAR, LARA 1
  1. 1 Universidad de Alcalá
    info

    Universidad de Alcalá

    Alcalá de Henares, España

    ROR https://ror.org/04pmn0e78

Editor: Zenodo

Año de publicación: 2024

Tipo: Dataset

CC BY 4.0

Resumen

This data gathers socioeconomic drivers at 1km2 grid cell spatial resolution to predict forest fires in a region in Spain. The response variable was fire density by grid cell from kernel density methods. It was produced under the Firemap project (https://geogra.uah.es/firemap/) by using GIS, spatial and statistical data sources at regional level in Spain. The resulting work was published at Vilar del Hoyo L, Martín Isabel MP, Martínez Vega FJ. 2011. Logistic regression models for human-caused wildfire risk estimation: analysing the effect of the spatial accuracy in fire occurrence data. European Journal of Forest Research. 130:983-96. doi: 10.1007/s10342-011-0488-2