Forest Fire Risk Prediction
Nolan, Rachael
Forest Fire Risk Prediction - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (235 p.)
Open Access
Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system.This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors.The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally.
Creative Commons
English
books978-3-0365-1473-4 9783036514741 9783036514734
10.3390/books978-3-0365-1473-4 doi
Research & information: general
Biology, life sciences
Forestry & related industries
fire danger rating fire management fire regime fire size fire weather Portugal critical LFMC threshold forest/grassland fire radiative transfer model remote sensing southwest China acid rain aerosol biomass burning forest fire PM2.5 direct estimation meteorological factor regression moisture content time lag forest fire driving factors forest fire occurrence random forest forest fire management China Cupressus sempervirens fire risk fuels fuel moisture content mass loss calorimeter Seiridium cardinale vulnerability to wildfires disease alien pathogen allochthonous species introduced fungus drying tests humidity diffusion coefficients wildfire prescribed burning modeling drought flammability fuel moisture leaf water potential plant traits climate change MNI fire season fire behavior crown fire fire modeling senescence foliar moisture content canopy bulk density fire danger fire weather patterns RCP FWI system SSR occurrence of forest fire machine learning variable importance prediction accuracy epicormic resprouter eucalyptus fire severity flammability feedbacks temperate forest n/a
Forest Fire Risk Prediction - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (235 p.)
Open Access
Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system.This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors.The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally.
Creative Commons
English
books978-3-0365-1473-4 9783036514741 9783036514734
10.3390/books978-3-0365-1473-4 doi
Research & information: general
Biology, life sciences
Forestry & related industries
fire danger rating fire management fire regime fire size fire weather Portugal critical LFMC threshold forest/grassland fire radiative transfer model remote sensing southwest China acid rain aerosol biomass burning forest fire PM2.5 direct estimation meteorological factor regression moisture content time lag forest fire driving factors forest fire occurrence random forest forest fire management China Cupressus sempervirens fire risk fuels fuel moisture content mass loss calorimeter Seiridium cardinale vulnerability to wildfires disease alien pathogen allochthonous species introduced fungus drying tests humidity diffusion coefficients wildfire prescribed burning modeling drought flammability fuel moisture leaf water potential plant traits climate change MNI fire season fire behavior crown fire fire modeling senescence foliar moisture content canopy bulk density fire danger fire weather patterns RCP FWI system SSR occurrence of forest fire machine learning variable importance prediction accuracy epicormic resprouter eucalyptus fire severity flammability feedbacks temperate forest n/a