Modeling wildland fire susceptibility using fuzzy systems

Ercanoglu M., WEBER K. T., LANGILLE J., NEVES R.

GISCIENCE & REMOTE SENSING, vol.43, no.3, pp.268-282, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 43 Issue: 3
  • Publication Date: 2006
  • Doi Number: 10.2747/1548-1603.43.3.268
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.268-282
  • Hacettepe University Affiliated: Yes


Due to fire suppression efforts, many areas have developed conditions whereby fire susceptibility is high. To help identify those areas and improve fire management, two fire susceptibility models were developed for a study area in southeastern Idaho. Both models used the same intrinsic parameters (topography, fuel characteristics, etc). The difference between the models is the first used expert knowledge to weight input parameters, whereas the second relied upon fuzzy systems to derive the weighting. Comparing the resulting output models indicates that the first more accurately capture fire susceptibility. This lends credibility to the use of expert knowledge in geo-spatial modeling.