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    张树深

    • 研究员     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:北京师范大学
    • 学位:硕士
    • 所在单位:环境学院
    • 电子邮箱:zhangss@dlut.edu.cn

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    The Study on Regional Environmental Risk Based on GIS Population Model (Retracted Article)

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    论文类型:会议论文

    发表时间:2011-01-01

    收录刊物:CPCI-S

    卷号:11

    关键字:Population density; Environmental risk assessment; Gis modeling; Remote sensing; Dalian

    摘要: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 hazard 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 Moran's 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 150 m, while 15637 and 13552 residents correspondingly within the state specified sanitary protection distance of 1 km buffering of SCIP and DHIP. Finally, there really exists a great difference between the number of residents under environmental hazard 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%. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Organizers of 2011 International Conference on Energy and Environmental Science.