Integration of Satellite Sensor Data, Fuel Type Maps and Meteorological Observations for Evaluation of Forest Fire Risk at the Pan-European Scale. Sebastián-López, A.; San-Miguel-Ayanz, J.; and Burgan, R. E. International Journal of Remote Sensing, 23(13):2713–2719, 2002.
doi  abstract   bibtex   
This letter presents an integrated model for the assessment of forest fire risk at the European scale that combines three data sources: meteorological data, remotely sensed data, and fuel type maps. Preliminary results on the validation of the fire risk model for the Mediterranean region are presented. Fire event data for 1995 and 1996 served as the basis for testing the model. The obtained results show that the model, which is referred to as Fire Potential Index (FPI), identifies well those areas at risk of fire. In agreement with an increasing fire risk, the slope of the FPI curve increases during the last few days prior to a fire event.
@article{sebastian-lopezIntegrationSatelliteSensor2002,
  title = {Integration of Satellite Sensor Data, Fuel Type Maps and Meteorological Observations for Evaluation of Forest Fire Risk at the Pan-{{European}} Scale},
  author = {{Sebasti{\'a}n-L{\'o}pez}, Ana and {San-Miguel-Ayanz}, Jes{\'u}s and Burgan, Robert E.},
  year = {2002},
  volume = {23},
  pages = {2713--2719},
  issn = {0143-1161},
  doi = {10.1080/01431160110107761},
  abstract = {This letter presents an integrated model for the assessment of forest fire risk at the European scale that combines three data sources: meteorological data, remotely sensed data, and fuel type maps. Preliminary results on the validation of the fire risk model for the Mediterranean region are presented. Fire event data for 1995 and 1996 served as the basis for testing the model. The obtained results show that the model, which is referred to as Fire Potential Index (FPI), identifies well those areas at risk of fire. In agreement with an increasing fire risk, the slope of the FPI curve increases during the last few days prior to a fire event.},
  journal = {International Journal of Remote Sensing},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14655938,europe,fire-danger,fire-fuel,forest-fires,forest-resources,integration-techniques,meteorology,remote-sensing},
  lccn = {INRMM-MiD:c-14655938},
  number = {13}
}
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