Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. A...Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.展开更多
Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate chan...Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate change for the region and provide a reference for applying adaptive measures for fire management. This study analyzed the changes in fire weather indices and the fire season under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5) for 2021-2050 using data from five global climate models together with observation data. The results showed that the analog data could project the average state of the climate for a given period but were not effective for simulating extreme weather conditions. Compared with the baseline period (1971-2000), the period 2021-2050 was predicted to have an increase in average temperature of 2.02-2.65?°C and in annual precipitation 25.4-40.3?mm, while the fire weather index (FWI) was predicted to increase by 6.2-11.2% and seasonal severity rating (SSR) by 5.5-17.2%. The DMC (Duff moisture code), ISI (initial spread index), BUI (build-up index), FWI and SSR were predicted to increase significantly under scenarios RCP4.5, RCP6.0, and RCP8.5. Furthermore, days with high or higher fire danger rating were predicted to be prolonged by 3-6?days, with the change in the southern region being greater under scenarios RCP4.5, RCP6.0, and RCP8.5.展开更多
A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground o...A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground on the uncertainty measure theory.Then the single-index measure function of sixteen influential factors and the calculation method of computing the index weight ground on entropy theory were respectively established.The value assignment of sixteen influential factors was carried out by the qualitative analysis and observational data, respectively, in succession.The sequence of fire danger class of four experimental coalfaces could be obtained by the computational aids of Matlab according to the confidence level criterion.Some conclusions that the fire danger class of the No.1, No.2 and No.3 coalface belongs to high criticality can be obtained.But the fire danger class of the No.4 coalface belongs to higher criticality.The fire danger class of the No.4 coalface is more than that of the No.2 coalface.The fire danger class of the No.2 coalface is more than that of the No.1 coalface.Finally, the fire danger class of the No.1 coalface is more than that of the No.3 coalface.展开更多
为建立适用于我国宏观区域的林火预警系统,以我国2000-2008年间发生的重大森林火灾为研究对象,利用MODIS数据估算森林可燃物的长势及含水量,与地理信息系统技术和数据库技术相结合,以火险指数作为预报林火发生等级的定量因子,研究并建...为建立适用于我国宏观区域的林火预警系统,以我国2000-2008年间发生的重大森林火灾为研究对象,利用MODIS数据估算森林可燃物的长势及含水量,与地理信息系统技术和数据库技术相结合,以火险指数作为预报林火发生等级的定量因子,研究并建立了林火预警模型;在商业遥感和GIS软件提供的二次开发平台下,利用Microsoft Visual Studio 2005语言,开发了林火预警系统。同时,利用选取的实验区及数据对预报方法和系统进行测试。结果表明:利用建立的林火预警系统所得的森林火险等级值,与实际发生的林火趋势基本一致;另外,火险指数可用作林火发生预警的定量分级因子。展开更多
文摘Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.
基金financially supported by the National Natural Science Foundation of China(31270695)the National Science and Technology Support Plan(2012BAC19B02)
文摘Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate change for the region and provide a reference for applying adaptive measures for fire management. This study analyzed the changes in fire weather indices and the fire season under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5) for 2021-2050 using data from five global climate models together with observation data. The results showed that the analog data could project the average state of the climate for a given period but were not effective for simulating extreme weather conditions. Compared with the baseline period (1971-2000), the period 2021-2050 was predicted to have an increase in average temperature of 2.02-2.65?°C and in annual precipitation 25.4-40.3?mm, while the fire weather index (FWI) was predicted to increase by 6.2-11.2% and seasonal severity rating (SSR) by 5.5-17.2%. The DMC (Duff moisture code), ISI (initial spread index), BUI (build-up index), FWI and SSR were predicted to increase significantly under scenarios RCP4.5, RCP6.0, and RCP8.5. Furthermore, days with high or higher fire danger rating were predicted to be prolonged by 3-6?days, with the change in the southern region being greater under scenarios RCP4.5, RCP6.0, and RCP8.5.
基金Supported by the National Foundation of China(50974055)the Program for Changjiang Scholars and Innovative Research Team in University(IRT0618)Henan Province Basic and Leading-edge Technology Research Program(082300463205)
文摘A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground on the uncertainty measure theory.Then the single-index measure function of sixteen influential factors and the calculation method of computing the index weight ground on entropy theory were respectively established.The value assignment of sixteen influential factors was carried out by the qualitative analysis and observational data, respectively, in succession.The sequence of fire danger class of four experimental coalfaces could be obtained by the computational aids of Matlab according to the confidence level criterion.Some conclusions that the fire danger class of the No.1, No.2 and No.3 coalface belongs to high criticality can be obtained.But the fire danger class of the No.4 coalface belongs to higher criticality.The fire danger class of the No.4 coalface is more than that of the No.2 coalface.The fire danger class of the No.2 coalface is more than that of the No.1 coalface.Finally, the fire danger class of the No.1 coalface is more than that of the No.3 coalface.
文摘为建立适用于我国宏观区域的林火预警系统,以我国2000-2008年间发生的重大森林火灾为研究对象,利用MODIS数据估算森林可燃物的长势及含水量,与地理信息系统技术和数据库技术相结合,以火险指数作为预报林火发生等级的定量因子,研究并建立了林火预警模型;在商业遥感和GIS软件提供的二次开发平台下,利用Microsoft Visual Studio 2005语言,开发了林火预警系统。同时,利用选取的实验区及数据对预报方法和系统进行测试。结果表明:利用建立的林火预警系统所得的森林火险等级值,与实际发生的林火趋势基本一致;另外,火险指数可用作林火发生预警的定量分级因子。
