Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility
Accurate identification of urban agglomeration spatial range is essential for scientific regional planning, optimal resource allocation, and sustainable development, forming the basis for regional development policy. To improve the accuracy of identifying urban agglomeration boundaries, this study f...
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2025-01-01
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| author | Yongwang Cao Qingpu Li Zaigao Yang |
| author_facet | Yongwang Cao Qingpu Li Zaigao Yang |
| author_sort | Yongwang Cao |
| collection | DOAJ |
| description | Accurate identification of urban agglomeration spatial range is essential for scientific regional planning, optimal resource allocation, and sustainable development, forming the basis for regional development policy. To improve the accuracy of identifying urban agglomeration boundaries, this study fuses nighttime light data, which reflects urban economic levels, with LandScan data representing population distribution and heatmap data indicating population mobility. This fusion allows for identification from a differentiated perspective of population distribution and mobility. We propose a new method for identifying the dynamic boundaries of urban agglomerations through multi-source data fusion. This method not only provides technical support for scientific regional planning but also effectively guides the functional positioning of edge cities and the optimization of resource allocation. The results show that the spatial range identified by NTL_LS has an accuracy of 80.37% and a kappa coefficient of 0.5225, while NTL_HM achieves an accuracy of 89.17% with a kappa coefficient of 0.7342, indicating that the fusion of economic level with population mobility data more accurately reflects the spatial range of urban agglomerations in line with real development patterns. By adopting a differentiated perspective on population distribution and mobility, we propose a new approach to identifying urban agglomeration spatial range. The research results based on this method provide more comprehensive and dynamic decision-making support for optimizing transportation layouts, allocating public resources rationally, and defining the functional positioning of edge cities. |
| format | Article |
| id | doaj-art-ece0ee2d546f4039a11edee915499587 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
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| series | Applied Sciences |
| spelling | doaj-art-ece0ee2d546f4039a11edee9154995872025-01-24T13:21:26ZengMDPI AGApplied Sciences2076-34172025-01-0115294510.3390/app15020945Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population MobilityYongwang Cao0Qingpu Li1Zaigao Yang2Guangzhou Academy of Social Sciences, Guangzhou 510410, ChinaInstitute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, ChinaGuangzhou Academy of Social Sciences, Guangzhou 510410, ChinaAccurate identification of urban agglomeration spatial range is essential for scientific regional planning, optimal resource allocation, and sustainable development, forming the basis for regional development policy. To improve the accuracy of identifying urban agglomeration boundaries, this study fuses nighttime light data, which reflects urban economic levels, with LandScan data representing population distribution and heatmap data indicating population mobility. This fusion allows for identification from a differentiated perspective of population distribution and mobility. We propose a new method for identifying the dynamic boundaries of urban agglomerations through multi-source data fusion. This method not only provides technical support for scientific regional planning but also effectively guides the functional positioning of edge cities and the optimization of resource allocation. The results show that the spatial range identified by NTL_LS has an accuracy of 80.37% and a kappa coefficient of 0.5225, while NTL_HM achieves an accuracy of 89.17% with a kappa coefficient of 0.7342, indicating that the fusion of economic level with population mobility data more accurately reflects the spatial range of urban agglomerations in line with real development patterns. By adopting a differentiated perspective on population distribution and mobility, we propose a new approach to identifying urban agglomeration spatial range. The research results based on this method provide more comprehensive and dynamic decision-making support for optimizing transportation layouts, allocating public resources rationally, and defining the functional positioning of edge cities.https://www.mdpi.com/2076-3417/15/2/945Pearl River Delta urban agglomerationurban spatial rangedifferentiationpopulation distributionpopulation mobility |
| spellingShingle | Yongwang Cao Qingpu Li Zaigao Yang Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility Applied Sciences Pearl River Delta urban agglomeration urban spatial range differentiation population distribution population mobility |
| title | Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility |
| title_full | Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility |
| title_fullStr | Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility |
| title_full_unstemmed | Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility |
| title_short | Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration from a Differentiated Perspective of Population Distribution and Population Mobility |
| title_sort | identifying the spatial range of the pearl river delta urban agglomeration from a differentiated perspective of population distribution and population mobility |
| topic | Pearl River Delta urban agglomeration urban spatial range differentiation population distribution population mobility |
| url | https://www.mdpi.com/2076-3417/15/2/945 |
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