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基于 POI 与夜间灯光数据的城乡边缘空间界定方法研究——以武汉市为例。

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

机构信息

Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430061, China.

Shenzhen Urban Space Planning and Architectural Design Co., Ltd., Shenzhen 518039, China.

出版信息

Int J Environ Res Public Health. 2023 Mar 1;20(5):4395. doi: 10.3390/ijerph20054395.

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, accounting for 17.30% of the total area of the city. Its land use types are mainly construction land, water area, and cultivated land, accounting for 40.75%, 30.03%, and 14.60% of the URF, respectively. Its NDVI and population density are at a medium level, with values of 1.630 and 2556.28 persons/km respectively; (4) the double mutation law of NPP and POI in urban and rural space confirms that the URF exists objectively as a regional entity generated in the process of urban expansion, provides empirical support for the theory of urban and rural ternary structure, and has a positive reference value for the allocation of global infrastructure, industrial division, ecological function division, and other researches.

摘要

城乡边缘区的边界划定是城市精细化规划和治理的基础工作,对促进全球可持续发展和城乡融合进程具有积极作用。过去,城乡边缘区的划定存在数据源单一、数据获取困难、时空分辨率低等缺点。本研究结合兴趣点(POI)和夜间灯光(NTL)数据,根据城乡空间结构特征,提出了一种新的城乡边缘区空间识别方法,并以武汉市为研究对象进行了实证分析,结合土地利用结构信息熵、NDVI 和人口密度数据对划定结果进行了验证和比较,并对典型区域进行了实地验证。结果表明:(1)POI 和 NTL 的融合可以最大限度地利用 POI 和 NTL 在设施类型、光强度和分辨率上的差异特征,与单独使用 POI、NTL 或人口密度数据识别城乡边缘区相比,更加准确和具有时效性;(2)NPP 和 POI(Suomi NPP-VIIRS 和 POI 的融合数据)可以定量识别城市的潜在中心区和多层结构,在武汉市城区核心区的波动范围在 0.2 到 0.6 之间,在新城镇群的波动范围在 0.1 到 0.3 之间,而在城乡边缘区和农村地区则急剧下降到 0.1 以下;(3)武汉市城乡边缘区总面积为 1482.35km²,占全市总面积的 17.30%。其土地利用类型主要为建设用地、水域和耕地,分别占城乡边缘区的 40.75%、30.03%和 14.60%。其 NDVI 和人口密度处于中等水平,分别为 1.630 和 2556.28 人/km²;(4)城乡空间中 NPP 和 POI 的双突变规律证实了城乡边缘区作为城市扩张过程中产生的区域实体客观存在,为城乡三元结构理论提供了实证支持,对全球基础设施配置、产业分工、生态功能分区等研究具有积极的参考价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eea6/10001591/9ceecaa939bd/ijerph-20-04395-g001.jpg

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