Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.landurbplan.2017.05.008 |
Understanding uneven urban expansion with natural cities using open data | |
Long, Ying1,2; Zhai, Weixin3,4; Shen, Yao5; Ye, Xinyue6 | |
2018-09-01 | |
发表期刊 | LANDSCAPE AND URBAN PLANNING |
ISSN | 0169-2046 |
EISSN | 1872-6062 |
出版年 | 2018 |
卷号 | 177页码:281-293 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA; England |
英文摘要 | The last several decades have witnessed a rapid yet uneven urban expansion in developing countries. The existing studies rely heavily on official statistical yearbooks and remote sensing images. However, the former data sources have been criticized due to its non-objectivity and low quality, while the latter is labor and cost consuming in most cases. Recent efforts made by fractal analyses provide alternatives to scrutinize the corresponding "natural urban area". In our proposed framework, the dynamics of internal urban contexts is reflected in a quasi-real-time manner using emerging new data and the expansion is a fractal concept instead of an absolute one based on the conventional Euclidean method. We then evaluate the magnitude and pattern of natural cities and their expansion in size and space. It turns out that the spatial expansion rate of official cities (OCs) in our study area China has been largely underestimated when compared with the results of natural cities (NCs). The perspective of NCs also provides a novel way to understanding the quality of uneven urban expansion. We detail our analysis for the 23 urban agglomerations in China, especially paying more attention to the three most dominating urban agglomerations of China: Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD). The findings from the OC method are not consistent with the NC method. The distinctions may arise from the definition of a city, and the bottom-up NC method contributes to our comprehensive understanding of uneven urban expansion. |
英文关键词 | Urban expansion Social media Head/tail division New data Open data China |
领域 | 资源环境 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000437967500026 |
WOS关键词 | LAND-USE CHANGE ; HEAD/TAIL BREAKS ; CHINA ; URBANIZATION ; DYNAMICS ; PATTERNS ; CITY ; EVOLUTION ; GROWTH |
WOS类目 | Ecology ; Environmental Studies ; Geography ; Geography, Physical ; Regional & Urban Planning ; Urban Studies |
WOS研究方向 | Environmental Sciences & Ecology ; Geography ; Physical Geography ; Public Administration ; Urban Studies |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/25178 |
专题 | 资源环境科学 |
作者单位 | 1.Tsinghua Univ, Sch Architecture, Beijing, Peoples R China; 2.Tsinghua Univ, Hang Lung Ctr Real Estate, Beijing, Peoples R China; 3.Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing, Peoples R China; 4.Univ N Carolina, Dept Geog & Earth Sci, Charlotte, NC USA; 5.UCL, London, England; 6.Kent State Univ, Kent, OH 44240 USA |
推荐引用方式 GB/T 7714 | Long, Ying,Zhai, Weixin,Shen, Yao,et al. Understanding uneven urban expansion with natural cities using open data[J]. LANDSCAPE AND URBAN PLANNING,2018,177:281-293. |
APA | Long, Ying,Zhai, Weixin,Shen, Yao,&Ye, Xinyue.(2018).Understanding uneven urban expansion with natural cities using open data.LANDSCAPE AND URBAN PLANNING,177,281-293. |
MLA | Long, Ying,et al."Understanding uneven urban expansion with natural cities using open data".LANDSCAPE AND URBAN PLANNING 177(2018):281-293. |
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