Smoothing with application to stochastic fire growth modelling
Modelling wildland fire spread stochastically is an important way to incorporate the uncertainty associated with this phenomenon. Fitting such a model to data from remote-sensed images could be used to provide accurate fire spread risk maps. We study a particular model from this perspective. One obj...
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| Language: | English |
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University of British Columbia
2017
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| Online Access: | http://hdl.handle.net/2429/62501 |