Proceedings Article | 7 October 2009
Jinxiang Xiao, Shu-E Huang, Anjian Zhong, Biqin Zhu, Qing Ye, Lijun Sun
KEYWORDS: Climatology, Vegetation, Remote sensing, Environmental sensing, Temperature metrology, Geographic information systems, Data modeling, Landsat, Combustion, Earth observing sensors
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.
