IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i18p8093-d1745195.html

Spatiotemporal Heterogeneity and Socioeconomic Drivers of Landscape Patterns in High-Density Communities of Wuhan

Author

Listed:
  • Wenjun Peng

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan 430068, China)

  • Dakun Dai

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Fuqin Liu

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan 430068, China)

  • Xu Wang

    (School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

High-density communities, characterized by concentrated populations and compact built environments, often exacerbate issues such as green space fragmentation, uneven distribution, and intensified urban heat island effects. Investigating the spatiotemporal heterogeneity and evolutionary characteristics of landscape patterns driven by population density (POP), road density (RD), street-level GDP (GDP S ), and nighttime light intensity (NTL) in Wuhan’s high-density communities using a geographically weighted regression (GWR) model is essential for informing sustainable urban planning strategies. The results showed that ED, PD, and SHDI exhibit consistent annual declines averaging 1.53%, 0.97% and 0.59%, respectively, while AI increased steadily at 0.11% per year. This indicates that human intervention has surpassed natural succession and become the dominant force in shaping landscape patterns. Among them, POP and RD are the direct driving factors for landscape pattern changes, while GDP S and NTL indirectly affect landscape patterns through economic structural adjustments and land use changes, forming differentiated spatial patterns in high-density communities. In terms of relationships, the GWR model performs better than ordinary least squares regression (OLS) by adjusting R 2 and residual Moran’s I, significantly improving its explanatory power. This study demonstrates the effectiveness of the GWR model in revealing the spatiotemporal heterogeneity between socioeconomic factors and landscape patterns, providing a transferable analytical framework for high-density cities. It thereby offers empirical and methodological support for addressing regional ecological constraints and advancing sustainable urban renewal.

Suggested Citation

  • Wenjun Peng & Dakun Dai & Fuqin Liu & Xu Wang, 2025. "Spatiotemporal Heterogeneity and Socioeconomic Drivers of Landscape Patterns in High-Density Communities of Wuhan," Sustainability, MDPI, vol. 17(18), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8093-:d:1745195
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/18/8093/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/18/8093/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hietel, Elke & Waldhardt, Rainer & Otte, Annette, 2007. "Statistical modeling of land-cover changes based on key socio-economic indicators," Ecological Economics, Elsevier, vol. 62(3-4), pages 496-507, May.
    2. Peters, Thomas A., 1989. "The exact moments of ols in dynamic regression models with non-normal errors," Journal of Econometrics, Elsevier, vol. 40(2), pages 279-305, February.
    3. Jae-Ik Kim & Myung-Jin Jun & Chang-Hwan Yeo & Ki-Hyun Kwon & Jun Yong Hyun, 2019. "The Effects of Land Use Zoning and Densification on Changes in Land Surface Temperature in Seoul," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    4. Veerkamp, Clara J. & Schipper, Aafke M. & Hedlund, Katarina & Lazarova, Tanya & Nordin, Amanda & Hanson, Helena I., 2021. "A review of studies assessing ecosystem services provided by urban green and blue infrastructure," Ecosystem Services, Elsevier, vol. 52(C).
    5. Jinliu Chen & Paola Pellegrini & Haoqi Wang, 2022. "Comparative Residents’ Satisfaction Evaluation for Socially Sustainable Regeneration—The Case of Two High-Density Communities in Suzhou," Land, MDPI, vol. 11(9), pages 1-16, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Remme, Roy P. & Meacham, Megan & Pellowe, Kara E. & Andersson, Erik & Guerry, Anne D. & Janke, Benjamin & Liu, Lingling & Lonsdorf, Eric & Li, Meng & Mao, Yuanyuan & Nootenboom, Christopher & Wu, Tong, 2024. "Aligning nature-based solutions with ecosystem services in the urban century," Ecosystem Services, Elsevier, vol. 66(C).
    2. Hui, Ling Chui & Jim, C.Y., 2022. "Urban-greenery demands are affected by perceptions of ecosystem services and disservices, and socio-demographic and environmental-cultural factors," Land Use Policy, Elsevier, vol. 120(C).
    3. Sanja Gašparović & Ana Sopina & Anton Zeneral, 2022. "Impacts of Zagreb’s Urban Development on Dynamic Changes in Stream Landscapes from Mid-Twentieth Century," Land, MDPI, vol. 11(5), pages 1-25, May.
    4. Zhang, Min & Wang, Jinman & Zhang, Yu & Wang, Jin, 2023. "Ecological response of land use change in a large opencast coal mine area of China," Resources Policy, Elsevier, vol. 82(C).
    5. Juraj Illes & Katarina Kristianova & Viera Joklova & Aida Shayegani, 2024. "Potential of Former Mill Race Corridors for Urban Regeneration Strategies—A Case Study from Podolínec in Prešov Region (Slovakia)," Land, MDPI, vol. 13(7), pages 1-19, July.
    6. Stanford, Garrett O. & Ferreira, Susana & Landry, Craig E. & Blachly, Ben, 2025. "Economic valuation of ecosystem services and natural infrastructure: A quantitative review of the literature," Ecosystem Services, Elsevier, vol. 75(C).
    7. Hisashi Tanizaki & Shigeyuki Hamori & Yoichi Matsubayashi, 2006. "On least-squares bias in the AR(p) models: Bias correction using the bootstrap methods," Statistical Papers, Springer, vol. 47(1), pages 109-124, January.
    8. Kiviet, Jan F. & Phillips, Garry D. A. & Schipp, Bernhard, 1999. "Alternative bias approximations in first-order dynamic reduced form models," Journal of Economic Dynamics and Control, Elsevier, vol. 23(7), pages 909-928, June.
    9. He-Ming Zeng & Louie Sieh & Dong Zhang & Hao Huang & Yu-Zun Zhang & Jin-Yeu Tsou, 2025. "Exploring the Impact of the Publicness of Public Space in Hong Kong: A Structural Equation Modelling Approach," Land, MDPI, vol. 14(1), pages 1-20, January.
    10. Adam Senetra & Marta Czaplicka & Małgorzata Dudzińska & Agnieszka Dawidowicz, 2024. "Functional and Aesthetic Factors for Well-Being in Age-Friendly Residential Areas (AFRA) in Poland: An International Comparative Perspective," Sustainability, MDPI, vol. 16(19), pages 1-25, October.
    11. Livia Bonciarelli & Fabio Orlandi & Desirée Muscas & Marco Fornaciari, 2025. "Sustainable Stormwater Management and Bioretention: An Overview of Reviews of the Last 10 Years," Land, MDPI, vol. 14(4), pages 1-28, March.
    12. Tianqi Zhang & Yue Zhou & Ming Li & Haoran Zhang & Tong Wang & Yu Tian, 2022. "Impacts of Urbanization on Drainage System Health and Sustainable Drainage Recommendations for Future Scenarios—A Small City Case in China," Sustainability, MDPI, vol. 14(24), pages 1-24, December.
    13. Eduardo Corbelle-Rico & Edelmiro López-Iglesias, 2024. "Farmland Abandonment and Afforestation—Socioeconomic and Biophysical Patterns of Land Use Change at the Municipal Level in Galicia, Northwest Spain," Land, MDPI, vol. 13(9), pages 1-19, August.
    14. Kathryn Rodgman, Mary & Anguelovski, Isabelle & Pérez-del-Pulgar, Carmen & Shokry, Galia & Garcia-Lamarca, Melissa & Connolly, James J.T. & Baró, Francesc & Triguero-Mas, Margarita, 2024. "Perceived urban ecosystem services and disservices in gentrifying neighborhoods: Contrasting views between community members and state informants," Ecosystem Services, Elsevier, vol. 65(C).
    15. Jinliu Chen & Kunlun Ren & Pengcheng Li & Haoqi Wang & Pu Zhou, 2026. "Toward effective urban regeneration post-COVID-19: Urban vitality assessment to evaluate people preferences and place settings integrating LBSNs and POI," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 28(4), pages 10047-10070, April.
    16. Shuyao Wu & Delong Li & Kai-di Liu & Wentao Zhang & Binbin V. Li & Shuangcheng Li & Lumeng Liu & Ximan Sun & Fangjin Xu & Jinwei Dong & Laibao Liu & Weili Duan & Zhonghao Zhang, 2026. "Ecosystem service demand relationship and trade-off patterns in urban parks across China," Papers 2602.11442, arXiv.org, revised Apr 2026.
    17. Mutoko, Morgan C. & Hein, Lars & Bartholomeus, Harm, 2014. "Integrated analysis of land use changes and their impacts on agrarian livelihoods in the western highlands of Kenya," Agricultural Systems, Elsevier, vol. 128(C), pages 1-12.
    18. Marchioni, Mariana & Raimondi, Franco & Becciu, Gianfranco & Dresti, Claudia, 2025. "Nature-based solutions for watershed management: An investigation on water-related ecosystem services delivery at multiple spatial scales," Ecosystem Services, Elsevier, vol. 73(C).
    19. Grzyb, Tomasz, 2024. "Mapping cultural ecosystem services of the urban riverscapes: the case of the Vistula River in Warsaw, Poland," Ecosystem Services, Elsevier, vol. 65(C).
    20. Savo, Valentina & D’Amato, Luca & Bartoli, Flavia & Zappitelli, Ilaria & Caneva, Giulia, 2025. "Evaluation of main regulating, provisioning, and supporting ecosystem services of urban street trees: A literature review," Ecosystem Services, Elsevier, vol. 71(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8093-:d:1745195. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.