Paper
7 October 2009 A study of forest fire danger district division in Lushan Mountain based on RS and GIS
Jinxiang Xiao, Shu-E Huang, Anjian Zhong, Biqin Zhu, Qing Ye, Lijun Sun
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Abstract
The study selected 9 factors, average maximum temperature, average temperature, average precipitation, average the longest days of continuous drought and average wind speed during fire prevention period, vegetation type, altitude, slope and aspect as the index of forest fire danger district division, which has taken the features of Lushan Mountain's forest fire history into consideration, then assigned subjective weights to each factor according to their sensitivity to fire or their fire-inducing capability. By remote sensing and GIS, vegetation information layer were gotten from Landsat TM image and DEM with a scale of 1:50000 was abstracted from the digital scanned relief map. Topography info. (elevation, slope, aspect) layers could be gotten after that. A climate resource databank that contained the data from the stations of Lushan Mountain and other nearby 7 stations was built up and extrapolated through the way of grid extrapolation in order to make the distribution map of climate resource. Finally synthetical district division maps were made by weighing and integrating all the single factor special layers,and the study area were divided into three forest fire danger district, include special fire danger district, I-fire danger district and II-fire danger district. It could be used as a basis for developing a forest fire prevention system, preparing the annual investment plan, allocating reasonably the investment of fire prevention, developing the program of forest fire prevention and handle, setting up forest fire brigade, leaders' decisions on forest fire prevention work.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jinxiang Xiao, Shu-E Huang, Anjian Zhong, Biqin Zhu, Qing Ye, and Lijun Sun "A study of forest fire danger district division in Lushan Mountain based on RS and GIS", Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 747822 (7 October 2009); https://doi.org/10.1117/12.829611
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KEYWORDS
Climatology

Vegetation

Environmental sensing

Remote sensing

Temperature metrology

Geographic information systems

Data modeling

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