Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations
Although measurements of urban shrinkage in China have received much attention, most have relied on statistical yearbook data based on political–administrative city boundaries, and remote-sensing-based quantification is mainly one-dimensional. This has caused problems in incorporating rural areas an...
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2025-07-01
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| author | Lin Chen Mingyue Liu Weidong Man |
| author_facet | Lin Chen Mingyue Liu Weidong Man |
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| description | Although measurements of urban shrinkage in China have received much attention, most have relied on statistical yearbook data based on political–administrative city boundaries, and remote-sensing-based quantification is mainly one-dimensional. This has caused problems in incorporating rural areas and spatiotemporal inconsistencies, as well as an inadequate understanding, which has subsequently resulted in an inaccurate shrinkage identification. This study merely utilized the latest multisensory and time-series remote sensing data, including nighttime light, land use, and population grids, to quantify the spatiotemporal patterns of multidimensional shrinkage based on the county-level urban entity mapping of Yangtze River Delta urban agglomerations (YRD-UAs) from 2003 to 2023. County-level urban entities were acquired from a pioneering mapping effort that utilized city-specific commuting distance and land use maps. The results demonstrated that urban entities in 215 counties grew at a generally slowing pace. The degree of economic, population, and space shrinkage was mainly slight, and the shrinking trajectory was dominated by temporary shrinkage. Most counties experienced population shrinkage in their coastal-oriented distribution, whereas economic shrinkage affected the fewest counties, with the lowest spatial clustering occurring northward. Population shrinkage also displayed the highest spatial autocorrelation, but its agglomeration weakened against space shrinkage clustering. This study concluded that the exclusive utilization of remote sensing products to measure urban-entity-based multidimensional shrinkage reduced the uncertainty associated with rural area inclusion and resulted in satisfactory assessment accuracy. The spatiotemporal patterns of multidimensional shrinkage suggested strengthening ecological land allocation within urban entities across the entire region, implementing polycentric development strategies in the north, as well as enhancing county-level economic governance in the northwest. This study presents a spatiotemporally comparable methodology for quantifying the multidimensional shrinking of county-level urban entities at a large scale and contributes to further optimizing the developments of YRD-UAs. |
| format | Article |
| id | doaj-art-9bab590c0a0a4730a33aeb40704672b2 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
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| spelling | doaj-art-9bab590c0a0a4730a33aeb40704672b22025-08-20T03:08:10ZengMDPI AGRemote Sensing2072-42922025-07-011714253610.3390/rs17142536Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban AgglomerationsLin Chen0Mingyue Liu1Weidong Man2Institute of Remote Sensing and Earth Sciences, School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, ChinaHebei Key Laboratory of Mining Development and Security Technology, Hebei Industrial Technology Institute of Mine Ecological Remediation, College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, ChinaHebei Key Laboratory of Mining Development and Security Technology, Hebei Industrial Technology Institute of Mine Ecological Remediation, College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, ChinaAlthough measurements of urban shrinkage in China have received much attention, most have relied on statistical yearbook data based on political–administrative city boundaries, and remote-sensing-based quantification is mainly one-dimensional. This has caused problems in incorporating rural areas and spatiotemporal inconsistencies, as well as an inadequate understanding, which has subsequently resulted in an inaccurate shrinkage identification. This study merely utilized the latest multisensory and time-series remote sensing data, including nighttime light, land use, and population grids, to quantify the spatiotemporal patterns of multidimensional shrinkage based on the county-level urban entity mapping of Yangtze River Delta urban agglomerations (YRD-UAs) from 2003 to 2023. County-level urban entities were acquired from a pioneering mapping effort that utilized city-specific commuting distance and land use maps. The results demonstrated that urban entities in 215 counties grew at a generally slowing pace. The degree of economic, population, and space shrinkage was mainly slight, and the shrinking trajectory was dominated by temporary shrinkage. Most counties experienced population shrinkage in their coastal-oriented distribution, whereas economic shrinkage affected the fewest counties, with the lowest spatial clustering occurring northward. Population shrinkage also displayed the highest spatial autocorrelation, but its agglomeration weakened against space shrinkage clustering. This study concluded that the exclusive utilization of remote sensing products to measure urban-entity-based multidimensional shrinkage reduced the uncertainty associated with rural area inclusion and resulted in satisfactory assessment accuracy. The spatiotemporal patterns of multidimensional shrinkage suggested strengthening ecological land allocation within urban entities across the entire region, implementing polycentric development strategies in the north, as well as enhancing county-level economic governance in the northwest. This study presents a spatiotemporally comparable methodology for quantifying the multidimensional shrinking of county-level urban entities at a large scale and contributes to further optimizing the developments of YRD-UAs.https://www.mdpi.com/2072-4292/17/14/2536county-level urban entitiesmultidimensional shrinking patternsnighttime light datapopulation gridsland use mapsYangtze River Delta urban agglomerations |
| spellingShingle | Lin Chen Mingyue Liu Weidong Man Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations Remote Sensing county-level urban entities multidimensional shrinking patterns nighttime light data population grids land use maps Yangtze River Delta urban agglomerations |
| title | Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations |
| title_full | Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations |
| title_fullStr | Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations |
| title_full_unstemmed | Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations |
| title_short | Multidimensional Identification of County-Level Shrinkage by Improved Mapping of Urban Entities Based on Time-Series Remote Sensing Data: A Case Study of Yangtze River Delta Urban Agglomerations |
| title_sort | multidimensional identification of county level shrinkage by improved mapping of urban entities based on time series remote sensing data a case study of yangtze river delta urban agglomerations |
| topic | county-level urban entities multidimensional shrinking patterns nighttime light data population grids land use maps Yangtze River Delta urban agglomerations |
| url | https://www.mdpi.com/2072-4292/17/14/2536 |
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