Learning-based prediction of wildfire spread with real-time rate of spread measurement-Reference-Cited by-同舟云学术

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Learning-based prediction of wildfire spread with real-time rate of spread measurement

Published:2020-05 Issue: Volume:215 Page:333-341
ISSN:0010-2180
Container-title:Combustion and Flame
language:en
Short-container-title:Combustion and Flame

Author:

Zhai Chunjie,Zhang Siyu,Cao Zhaolou,Wang Xinmeng

Funder

National Key R D Program of China

Nanjing Forest Police College Pre-research Project

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Reference38 articles.

1. Real-time wildland fire spread modeling using tabulated flame properties;Gennaro;Fire Saf. J.,2017

2. Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour;Yassemi;Ecol. Model.,2008

3. Weather, fuels, and topography impede wildland fire spread in western US landscapes;Holsinger;Forest Ecol. Manag.,2016

4. Negative consequences of positive feedbacks in US wildfire management;Calkin;Forest Ecosyst.,2015

5. Vegetation and topography interact with weather to drive the spatial distribution of wildfires in the eastern boreal forest of Canada;Cavard;Int. J. Wildland Fire,2015

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