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Titel |
A stochastic Forest Fire Model for future land cover scenarios assessment |
VerfasserIn |
M. D'Andrea, P. Fiorucci, T. P. Holmes |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1561-8633
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Digitales Dokument |
URL |
Erschienen |
In: Natural Hazards and Earth System Science ; 10, no. 10 ; Nr. 10, no. 10 (2010-10-13), S.2161-2167 |
Datensatznummer |
250008448
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Publikation (Nr.) |
copernicus.org/nhess-10-2161-2010.pdf |
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Zusammenfassung |
Land cover is affected by many factors including economic
development, climate and natural disturbances such as wildfires. The
ability to evaluate how fire regimes may alter future vegetation,
and how future vegetation may alter fire regimes, would assist
forest managers in planning management actions to be carried out in
the face of anticipated socio-economic and climatic change. In this
paper, we present a method for calibrating a cellular automata
wildfire regime simulation model with actual data on land cover and
wildfire size-frequency. The method is based on the observation that
many forest fire regimes, in different forest types and regions,
exhibit power law frequency-area distributions. The standard
Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM)
produces simulations which reproduce this observed pattern. However,
the standard model is simplistic in that it considers land cover to
be binary – each cell either contains a tree or it is empty – and
the model overestimates the frequency of large fires relative to
actual landscapes. Our new model, the Modified Forest Fire Model
(MFFM), addresses this limitation by incorporating information on
actual land use and differentiating among various types of flammable
vegetation. The MFFM simulation model was tested on forest types
with Mediterranean and sub-tropical fire regimes. The results showed
that the MFFM was able to reproduce structural fire regime
parameters for these two regions. Further, the model was used to
forecast future land cover. Future research will extend this model
to refine the forecasts of future land cover and fire regime
scenarios under climate, land use and socio-economic change. |
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