Evidence map›Paper›PMID 36901406›Full record

ArticleInternational journal of environmental research and public health2023

Research on Spatial Delineation Method of Urban-Rural Fringe Combining POI and Nighttime Light Data-Taking Wuhan City as an Example.

Jing Yu, Yingying Meng, Size Zhou, Huaiwen Zeng, Ming Li, Zhaoxia Chen, Yan Nie

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Jing YuHubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.
Yingying MengHubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.
Size ZhouHubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.
Huaiwen ZengShenzhen Urban Space Planning and Architectural Design Co., Ltd., Shenzhen 518039, China.
Ming LiHubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.
Zhaoxia ChenHubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.
Yan NieHubei Provincial Key Laboratory for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430062, China.

Funding

National Social Science Foundation 15BTQ082
6 · The paper itself

Abstract

The boundary delineation of the urban-rural fringe (URF) is the basic work of fine planning and governance of cities, which plays a positive role in promoting the process of global sustainable development and urban and rural integration. In the past, the delineation of URF had shortcomings such as a single selected data source, difficulty in obtaining data, and low spatial and temporal resolution. This study combines Point of Interest (POI) and Nighttime Light (NTL) data, proposes a new spatial recognition method of URF according to the characteristics of urban and rural spatial structure, and conducts empirical analysis with Wuhan as the research object, combining the information entropy of land use structure, NDVI, and population density data to verify and compare the delineation results and field verification was conducted for typical areas. The results show that (1) the fusion of POI and NTL can maximize the use of the characteristics of the differences in facility types, light intensity, and resolution between POI and NTL, compared with the urban-rural fringe boundary identified by POI, NTL or population density data alone, and it is more accurate and time-sensitive; (2) NPP and POI (fusion data of Suomi NPP-VIIRS and POI) can quantitatively identify potential central area and multi-layer structure of the city. It fluctuates between 0.2 and 0.6 in the urban core area of Wuhan and between 0.1 and 0.3 in the new town clusters, while in the URF and rural areas drops sharply to below 0.1; (3) the urban-rural fringe area of Wuhan covers a total area of 1482.35 km

Indexed as

LightRural PopulationChinaCitiesHumansIndustrySustainable Developmentbreaking point analysis methodNPP and POI composite indexurban and rural spatial structureurban-rural fringe

Identifiers

PMID36901406
PMCPMC10001591

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