Spatial Analysis of Urban Thermal Environment Based on Grey Clustering Method
Spatial Analysis of Urban Thermal Environment Based on Grey Clustering Method
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DOI：
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发表时间：
2012
影响因子：
11.4
通讯作者：
Zhang Yi-han
中科院分区：
文献类型：
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作者：
Zhang Yi-han
随着城市化和全球变暖的快速发展，城市热环境越来越受到人们的关注。城市热环境被认为是不可预测的，属于灰色系统，可以对热环境的几个驱动因素进行灰色优势分析。以广州南部某地区为例进行了实验分析，结果表明，城市化水平是导致该地区气温上升的决定性因素之一，分析还表明，空间城市化与热过敏区是一致的；此外，绿地指数、地表湿度和工业用地比率也是影响因素。另一方面，GDP强度、人口密度和工农业总产值强度的灰色关联系数较低。进一步研究了基于灰色优势分析的灰色聚类法的优化。与遥感地表温度反演相比，总的符合率为83%。灰色聚类法存在一些主观因素，如白化权函数的确定问题和遥感数据的不确定性，因此，应努力提高其定量精度。
More and more concerns have been attached to urban thermal environment due to the rapid development of urbanization and global warming.Urban thermal environment is regarded as being inscrutable so it belongs to grey system and the grey advantage analysis can be made with several driving factors of thermal environment.An experimental analysis was conducted in an area of south part of Guangzhou,and the result showed that the level of urbanization was the decisive factor,among other things,that led to rising temperature in the study area.The analysis also suggested that the spatial urbanization was coincided with the thermal over-stressing area;in addition,the green land index followed by earth surface humidity and the industrial land ratio were the influencing factors as well.On the other hand,the grey correlation coefficients of GDP intensity,density of population and the intensity of gross industrial and agricultural output were comparatively low.A further study conducted was about the optimization of grey clustering method on the basis of grey advantage analysis.Compared with the remote-sensing land surface temperature inversion,the total co-incidence rate was 83%.There exist some subjective factors with the grey clustering method,such as the problem with ascertaining the whitenization weight function and the uncertainty of remote-sensing data,therefore efforts should be made to upgrade its quantitative precision.