Space-Time Fractal Properties of the Forest-Fire Series in Central Italy. Telesca, L.; Amatucci, G.; Lasaponara, R.; Lovallo, M.; and Rodrigues, M. J. 12(7):1326–1333.
Space-Time Fractal Properties of the Forest-Fire Series in Central Italy [link]Paper  doi  abstract   bibtex   
The space-time fractality of the forest-fire sequence (1997-2003) occurred in the Tuscany Region (central Italy), one of the most vulnerable to wildfires in Italy, has been approached by using spatial and temporal fractal tools. The fractal exponent α, estimated by the Fano factor method, characterises the time-clustering behaviour of the set of fires, while the correlation dimension Dc, calculated by means of the correlation integral method, gives information on the space-clustering behaviour of the sequence of fires. We found that (i) the investigated fire set is globally characterized by space-time clustering behaviour; (ii) α and Dc decreases and increases, respectively with the increase of the threshold size of burned area; (iii) the time variation of α shows a tendency towards Poissonian processes in correspondence of the largest events.
@article{telescaSpacetimeFractalProperties2007,
  title = {Space-Time Fractal Properties of the Forest-Fire Series in Central {{Italy}}},
  author = {Telesca, Luciano and Amatucci, Giuseppe and Lasaponara, Rosa and Lovallo, Michele and Rodrigues, Maria J.},
  date = {2007-10},
  journaltitle = {Communications in Nonlinear Science and Numerical Simulation},
  volume = {12},
  pages = {1326--1333},
  issn = {1007-5704},
  doi = {10.1016/j.cnsns.2005.12.003},
  url = {https://doi.org/10.1016/j.cnsns.2005.12.003},
  abstract = {The space-time fractality of the forest-fire sequence (1997-2003) occurred in the Tuscany Region (central Italy), one of the most vulnerable to wildfires in Italy, has been approached by using spatial and temporal fractal tools. The fractal exponent α, estimated by the Fano factor method, characterises the time-clustering behaviour of the set of fires, while the correlation dimension Dc, calculated by means of the correlation integral method, gives information on the space-clustering behaviour of the sequence of fires. We found that (i) the investigated fire set is globally characterized by space-time clustering behaviour; (ii) α and Dc decreases and increases, respectively with the increase of the threshold size of burned area; (iii) the time variation of α shows a tendency towards Poissonian processes in correspondence of the largest events.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13350410,clustering,forest-fires,forest-resources,fractal,italy,non-linearity,spatio-temporal-scale,statistics},
  number = {7}
}
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