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本科生林玥的论文在Environment and Planning B: Urban Analytics and City Science 刊出
发布时间:2019-12-23     发布者:易真         审核者:     浏览次数:

标题: Spatial pattern analysis of address quality: A study on the impact of rapid urban expansion in China

作者: Yue Lin,Mengjun Kang,Biao He

来源出版物: Environment and Planning B: Urban Analytics and City Science DOI: doi/10.1177/2399808319895272  出版年: December 18, 2019

摘要: Standard address data are essential geographical information that play an important role in urban management. However, due to the complex structures of Chinese addresses, poor address quality has long been a problem in China. Although several measures were established to improve the address quality, nonstandard address data are still common in new urban areas. To investigate the potential causes of the geographical disparities in address quality, in this paper, we hypothesize that the sprawling urban form caused by rapid urban expansion in China has hindered the generation of standard addresses in new urban areas. To test this hypothesis, the spatial pattern of address quality in Shenzhen, China, is analyzed, and the potential causal paths relating urban expansion, urban form, and address quality are examined using structural equation modeling. The results indicate poorer address quality in new urban areas in Shenzhen. Rapid urban expansion has an indirect negative relation with the address quality. In addition, both road compactness and land use compactness have a direct positive effect on address quality, but the latter is insignificant. In this case, to facilitate improvements in address quality, a plan with dense and small blocks is suggested in the planning of new urban areas.

作者关键词:Address quality, geocoding service, LISA, structural equation modeling, urban form

地址:

[Yue Lin,Mengjun Kang] Wuhan University, China

[Yue Lin] The Ohio State University, USA

[Biao He] Shenzhen University, Chin

通讯作者地址: Mengjun Kang: School of Resource and Environmental Science, Wuhan University, Wuhan, China.

电子邮件地址: mengjunk@whu.edu.cn

影响因子:2.825