Using boosted regression trees to analyze the factors affecting the spatial distribution pattern of wildfire in China
Determining factors that affect the spatial distribution pattern of wildfires has significant implications for wildfire prediction and fire risk zonation,and could also provide scientific basis for making rational wildfire management decisions as well.We chose five factors including annual average temperature,mean annual precipitation,elevation,vegetation type and population density,and utilized boosted regression tree (BRT) method to analyze the main factors that influence the spatial distribution pattern of burned area and the number of fires from 2006 to 2011.Results showed that the factor most affecting the spatial distribution of burned area according to its relative contribution was elevation (36.92％),followed by annual average temperature (27.85％),mean annual precipitation (13.17％),population density (13.00％) and vegetation type (9.07％).In general,climate and elevation determined the spatial distribution pattern of burned area.The factor most affecting the spatial distribution of the number of fires according to its contribution was population density (27.44％),followed by elevation (25.97％),vegetation types (22.84％),annual average temperature (18.98％) and mean annual precipitation (4.77％) according to their relative contributions.Human activities together with topography and fuels determined the spatial distribution pattern of the number of fires.We suggested that,in addition to climate and vegetation factors,topographic factors especially elevation should be included when making national wildfire risk zonation;and that the management of field fire use should be strengthened and fuel treatment be performed to reduce the occurrence of wildfires.
国家科技期刊平台
NSTL
万方数据
维普
