@article{fdi:010057009,
  title = {{E}nvironmental susceptibility model for predicting forest fire occurrence in the {W}estern {G}hats of {I}ndia},
  author = {{R}enard, {Q}. and {P}{\'e}lissier, {R}apha{\¨e}l and {R}amesh, {B}. {R}. and {K}odandapani, {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}orest fires are a recurrent management problem in the {W}estern {G}hats of {I}ndia. {A}lthough most fires occur during the dry season, information on the spatial distribution of fires is needed to improve fire prevention. {W}e used the {MODIS} {H}otspots database and {M}axent algorithm to provide a quantitative understanding of the environmental controls regulating the spatial distribution of forest fires over the period 2003-07 in the entire {W}estern {G}hats and in two nested subregions with contrasting characteristics. {W}e used hierarchical partitioning to assess the independent contributions of climate, topography and vegetation to the goodness-of-fit of models and to build the most parsimonious fire susceptibility model in each study area. {R}esults show that although areas predicted as highly prone to forest fires were mainly localised on the eastern slopes of the {G}hats, spatial predictions and model accuracies differed significantly between study areas. {W}e suggest accordingly a two-step approach to identify: first, large fire-prone areas by paying special attention to the climatic conditions of the monsoon season before the fire season, which determine the fuels moisture content during the fire season; second, the most vulnerable sites within the fire-prone areas using local models mainly based on the type of vegetation.},
  keywords = {environmental controls ; fire susceptibility model ; {M}axent ; {MODIS} ; nested study areas},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {W}ildland {F}ire},
  volume = {21},
  numero = {4},
  pages = {368--379},
  ISSN = {1049-8001},
  year = {2012},
  DOI = {10.1071/wf10109},
  URL = {https://www.documentation.ird.fr/hor/fdi:010057009},
}