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杜清运实验室博士生聂可的论文在Sustainability刊出
发布时间:2015-03-05 08:38:04     发布者:yz     浏览次数:

标题:A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China作者:Nie Ke; Wang Zhensheng; Du Qingyun; Ren Fu; Tian Qin

来源出版物:Sustainability 卷:7 期:3 页:2662-2677 DOI:10.3390/su7032662 出版年:4 March 2015

摘要:Research on spatial cluster detection of traffic crash (TC) at the city level plays an essential role in safety improvement and urban development. This study aimed to detect spatial cluster pattern and identify riskier road segments (RRSs) of TC constrained by network with a two-step integrated method, called NKDE-GLINCS combining density estimation and spatial autocorrelation. The first step is novel and involves in spreading TC count to a density surface using Network-constrained Kernel Density Estimation (NKDE). The second step is the process of calculating local indicators of spatial association (LISA) using Network-constrained Getis-Ord Gi* (GLINCS). GLINCS takes the smoothed TC density as input value to identify locations of road segments with high risk. This method was tested using the TC data in 2007 in Wuhan, China. The results demonstrated that the method was valid to delineate TC cluster and identify risk road segments. Besides, it was more effective compared with traditional GLINCS using TC counting as input. Moreover, the top 20 road segments with high-high TC density at the significance level of 0.1 were listed. These results can promote a better identification of RRS, which is valuable in the pursuit of improving transit safety and sustainability in urban road network. Further research should address spatial-temporal analysis and TC factors exploration.

文献类型:Article

语种:English

作者关键词:network-constrained;spatial cluster pattern;traffic crash;Kernel Density Estimation;Getis-Ord Gi;riskier road segments

通讯作者地址:Du Qingyun; School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079,China

电子邮件地址:qydu@whu.edu.cn

地址:

[Nie Ke; Wang Zhensheng; Du Qingyun; Ren Fu; Tian Qin]School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079,China

[Nie Ke; Wang Zhensheng; Du Qingyun; Ren Fu; Tian Qin] Key Laboratory of GIS, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan 430079, China

ISSN:2071-1050

全文链接:http://www.mdpi.com/2071-1050/7/3/2662

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