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Fine-Scale Identification and Functional Coupling Coordination of Production-Living-Ecological Space in Fuzhou's Rapid Urbanization Area, China.

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Title: Fine-Scale Identification and Functional Coupling Coordination of Production-Living-Ecological Space in Fuzhou's Rapid Urbanization Area, China.
Authors: Lu, Chunyan1,2 (AUTHOR) luchunyan@fafu.edu.cn, Chen, Luyan1,2 (AUTHOR), Li, Xinping1 (AUTHOR), Huang, Zhihuang1,2 (AUTHOR), Yan, Zhanyou1 (AUTHOR)
Source: Remote Sensing. Aug2026, Vol. 18 Issue 16, p2721. 28p.
Subjects: Geospatial data, Socioeconomic factors, Urbanization, Cities & towns, Remote sensing, Geographic spatial analysis
Geographic Terms: China, Fuzhou Fu (Fujian Sheng, China)
Abstract: Highlights: What are the main findings? The comprehensive PLES function of the study area increased markedly, and urban zones exhibit higher average comprehensive PLES function values than rural zones in the cell grid, indicating evident urban-rural functional heterogeneity. From 2012 to 2024, all PLES functional combinations experienced steady improvements in coupling coordination; socioeconomic factors serve as the dominant driving force to mitigate inter-functional conflicts and facilitate coordinated development. What are the implications of the main findings? The integrated CCDM-GeoDetector framework based on multi-source geospatial data provides a replicable technical paradigm for evaluating territorial functional coordination in rapidly urbanized regions. The revealed urban-rural functional structure differentiation and coordinated evolution characteristics support differentiated zoning governance to balance urban construction, living demand, and ecological conservation. Accelerated urban expansion and socioeconomic growth have led to substantial changes in territorial spatial organization and growing pressures among spatial functions. Therefore, conducting fine-scale identification, functional evaluation, and coordination analysis of production-living-ecological space (PLES) carries practical value for improving spatial allocation and fostering harmonious regional coordination. By integrating remote sensing imagery and point-of-interest (POI) data, this study employed a hierarchical identification method combining the object-oriented random forest method with the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to map the PLES spatiotemporal evolution in Fuzhou's rapidly urbanizing territory over the 2012–2024 period. PLES functions were quantitatively assessed through a comprehensive evaluation index system, while the standard deviation ellipse, GeoDetector, and coupling coordination degree models were further employed to reveal their evolutionary patterns, driving mechanisms, and synergistic interactions. The results indicated that ecological-dominated spaces occupied the dominant share (nearly 63%). Meanwhile, living-dominated spaces expanded significantly, growing by 68.93 km2 during the study period. The PLES comprehensive function increased by 15.50%, with the living function and production function rising by 57.19% and 61.84%, respectively. Distinct spatial differentiation existed in PLES functions across urban and rural territories, shaping mutually complementary functional systems. The coupling coordination level of PLES functions continuously improved, although notable regional disparities existed, with highly coordinated areas concentrated in midwestern urban areas. PLES functional evolution was jointly driven by natural and socioeconomic factors, which interacted through nonlinear or two-factor enhancement effects. This study provides a replicable methodological framework for fine-scale PLES research and offers scientific support for regional spatial governance and high-quality coordinated development. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Fine-Scale Identification and Functional Coupling Coordination of Production-Living-Ecological Space in Fuzhou's Rapid Urbanization Area, China.
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2026, Vol. 18 Issue 16, p2721. 28p.
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzhou+Fu+%28Fujian+Sheng%2C+China%29%22">Fuzhou Fu (Fujian Sheng, China)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights: What are the main findings? The comprehensive PLES function of the study area increased markedly, and urban zones exhibit higher average comprehensive PLES function values than rural zones in the cell grid, indicating evident urban-rural functional heterogeneity. From 2012 to 2024, all PLES functional combinations experienced steady improvements in coupling coordination; socioeconomic factors serve as the dominant driving force to mitigate inter-functional conflicts and facilitate coordinated development. What are the implications of the main findings? The integrated CCDM-GeoDetector framework based on multi-source geospatial data provides a replicable technical paradigm for evaluating territorial functional coordination in rapidly urbanized regions. The revealed urban-rural functional structure differentiation and coordinated evolution characteristics support differentiated zoning governance to balance urban construction, living demand, and ecological conservation. Accelerated urban expansion and socioeconomic growth have led to substantial changes in territorial spatial organization and growing pressures among spatial functions. Therefore, conducting fine-scale identification, functional evaluation, and coordination analysis of production-living-ecological space (PLES) carries practical value for improving spatial allocation and fostering harmonious regional coordination. By integrating remote sensing imagery and point-of-interest (POI) data, this study employed a hierarchical identification method combining the object-oriented random forest method with the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to map the PLES spatiotemporal evolution in Fuzhou's rapidly urbanizing territory over the 2012–2024 period. PLES functions were quantitatively assessed through a comprehensive evaluation index system, while the standard deviation ellipse, GeoDetector, and coupling coordination degree models were further employed to reveal their evolutionary patterns, driving mechanisms, and synergistic interactions. The results indicated that ecological-dominated spaces occupied the dominant share (nearly 63%). Meanwhile, living-dominated spaces expanded significantly, growing by 68.93 km2 during the study period. The PLES comprehensive function increased by 15.50%, with the living function and production function rising by 57.19% and 61.84%, respectively. Distinct spatial differentiation existed in PLES functions across urban and rural territories, shaping mutually complementary functional systems. The coupling coordination level of PLES functions continuously improved, although notable regional disparities existed, with highly coordinated areas concentrated in midwestern urban areas. PLES functional evolution was jointly driven by natural and socioeconomic factors, which interacted through nonlinear or two-factor enhancement effects. This study provides a replicable methodological framework for fine-scale PLES research and offers scientific support for regional spatial governance and high-quality coordinated development. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.3390/rs18162721
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      – Code: eng
        Text: English
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        PageCount: 28
        StartPage: 2721
    Subjects:
      – SubjectFull: Geospatial data
        Type: general
      – SubjectFull: Socioeconomic factors
        Type: general
      – SubjectFull: Urbanization
        Type: general
      – SubjectFull: Cities & towns
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      – SubjectFull: Remote sensing
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      – SubjectFull: Geographic spatial analysis
        Type: general
      – SubjectFull: China
        Type: general
      – SubjectFull: Fuzhou Fu (Fujian Sheng, China)
        Type: general
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      – TitleFull: Fine-Scale Identification and Functional Coupling Coordination of Production-Living-Ecological Space in Fuzhou's Rapid Urbanization Area, China.
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            NameFull: Lu, Chunyan
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              Text: Aug2026
              Type: published
              Y: 2026
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