The Study on Regional Environmental Risk Based on GIS Population Model
The results of environmental risk accidents have important relations with the spatial distribution of population. In this paper, by combining the habitations extracted from the ALOS remote sensing images in 2008 with the statistical population data of Dalian, the author simulated the population density based on GIS modeling. The average relative error between GIS-based simulation results of population and statistical data is 9.78％, the accuracy is high, and simulation results could reflect the actual spatial distribution of population. The population distribution and HOTSPOT are analyzed, which are followed by calculating the number of residents under environmental hazards within fire protection distance and sanitary protection zone of Songmudao Chemical Industry Park (SCIP) and Dagushan Harbor Industrial Park (DHIP). Specific research conclusions are as followed: Firstly, the distribution of Dalian population density has showed an apparent spatial autocorrelation with the test value of Morans I being 0.86. Secondly, there is a strong heterogeneous trend of population density and seven HOTSPOTS are founded including Dalian metropolis, Jinzhou urban area Maqiaozi of Dalian Development Area, urban zone in Lushun, the urban area of Wafangdian, Pulandian and Zhuanghe City. Thirdly, there are 7603 and 1332 residents within the state specified fire protection distance of 150m, while 15637 and 13552 residents correspondingly within the state specified sanitary protection distance of lkm buffering of SCIP and DHIP. Finally, there really exists a great difference between the number of residents under environmental hazards calculated by statistical population data and population density results which are stimulated by GIS modeling, the average relative error of the results is up to 81.4％.
population density environmental risk assessment gis modeling remote sensing Dalian
Yijun Fan Guobao Song Shushen Zhang Zhaoyang Feng
Key Laboratory oflndustrial Ecology and Environmental Engineering, MOESchool of Environmental and Bi Key Laboratory oflndustrial Ecology and Environmental Engineering, MOESchool of Environmental and Bi Institute of Ecology Chinese Research Academy of Environmental Sciences Beijing, China
国际会议
昆明
英文
253-257
2010-10-17（万方平台首次上网日期，不代表论文的发表时间）