Extracting physical urban areas of 81 major Chinese cities from high-resolution land uses. (December 2022)
- Record Type:
- Journal Article
- Title:
- Extracting physical urban areas of 81 major Chinese cities from high-resolution land uses. (December 2022)
- Main Title:
- Extracting physical urban areas of 81 major Chinese cities from high-resolution land uses
- Authors:
- Zhang, Xiuyuan
Du, Shihong
Zhou, Yuyu
Xu, Yun - Abstract:
- Abstract: Past two decades have witnessed a rapid urbanization process in China, with the urbanization ratio suddenly increasing from 30.9 % to 63.9 %. Physical urban areas (PUA) are fundamental indicators to monitoring and evaluating urbanization, which differ from administrative urban areas and are much complicated to identify, as PUA contain heterogeneous land uses which are shaped by variant physical structures and diverse socioeconomic activities. Previous studies extracted PUA by densely populated, night-lighted, built-up, or artificial impervious surfaces, which consider either physical or socioeconomic aspect of PUA, but cannot measure both. Accordingly, this study firstly integrates physical and socioeconomic features derived from high-resolution (HR) satellite images and points of interests (POI) to extract HR land uses; then, a knowledge-based morphological aggregation method is proposed to aggregate different land uses and generate PUA based on spatial land-use structures. As the result, 450 PUA in 81 major Chinese cities are extracted and a China PUA dataset (namely CPUA) is generated. The CPUA is evaluated by reference to a widely-used global urban boundary dataset. The evaluation shows an accuracy of 92.5 %, demonstrating the effectiveness of the proposed method and the reliability of generated dataset. The evaluation also indicates that the generated CPUA outperforms the reference dataset in identifying urban parks and eliminating rural homesteads.Abstract: Past two decades have witnessed a rapid urbanization process in China, with the urbanization ratio suddenly increasing from 30.9 % to 63.9 %. Physical urban areas (PUA) are fundamental indicators to monitoring and evaluating urbanization, which differ from administrative urban areas and are much complicated to identify, as PUA contain heterogeneous land uses which are shaped by variant physical structures and diverse socioeconomic activities. Previous studies extracted PUA by densely populated, night-lighted, built-up, or artificial impervious surfaces, which consider either physical or socioeconomic aspect of PUA, but cannot measure both. Accordingly, this study firstly integrates physical and socioeconomic features derived from high-resolution (HR) satellite images and points of interests (POI) to extract HR land uses; then, a knowledge-based morphological aggregation method is proposed to aggregate different land uses and generate PUA based on spatial land-use structures. As the result, 450 PUA in 81 major Chinese cities are extracted and a China PUA dataset (namely CPUA) is generated. The CPUA is evaluated by reference to a widely-used global urban boundary dataset. The evaluation shows an accuracy of 92.5 %, demonstrating the effectiveness of the proposed method and the reliability of generated dataset. The evaluation also indicates that the generated CPUA outperforms the reference dataset in identifying urban parks and eliminating rural homesteads. Furthermore, the CPUA can be employed as fundamental data to monitor urbanization process and its spatial patterns, and thus plays an important role in evaluating sustainable city development. The CPUA is freely available on http://geoscape.pku.edu.cn/otherdata_en.html . Highlights: FIRST work to identify physical urban areas (PUA) from a land use perspective Proposes a multimodal land-use segmentation method to extract land uses Proposes a morphological aggregation method to delineate PUA based on land uses Generates a PUA dataset for 81 major Chinese cities, namely CPUA … (more)
- Is Part Of:
- Cities. Volume 131(2022)
- Journal:
- Cities
- Issue:
- Volume 131(2022)
- Issue Display:
- Volume 131, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 131
- Issue:
- 2022
- Issue Sort Value:
- 2022-0131-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12
- Subjects:
- Urban -- Land use -- Physical urban area -- China physical urban area (CPUA) -- Multimodal land use segmentation
City planning -- Periodicals
Urban policy -- Periodicals
711.4 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02642751 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cities.2022.104061 ↗
- Languages:
- English
- ISSNs:
- 0264-2751
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3267.792160
British Library DSC - BLDSS-3PM
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