IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4347-d1653459.html
   My bibliography  Save this article

Study on the Relationship Between 3D Landscape Patterns and Residents’ Comfort in Urban Multi-Unit High-Rise Residential Areas: A Case Study of High-Density Inland City

Author

Listed:
  • Yaoyun Zhang

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Ge Shi

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Ziying Feng

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Entao Zheng

    (Zhejiang Shuzhi Space Planning and Design Co., Ltd., Hangzhou 310030, China)

  • Chuang Chen

    (Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Xinyu Li

    (School of Civil Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Difan Yu

    (School of Civil Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Yunpeng Zhang

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

Abstract

As urbanization accelerates, the increasing density of urban buildings and the prevalence of multi-unit high-rise residential areas have emerged as significant factors affecting residents’ comfort. Effective green space planning within residential areas can mitigate residents’ thermal discomfort. This study utilizes methods including the construction of two-dimensional and three-dimensional landscape indices and meteorological data simulation to examine the relationship between residents’ comfort levels at various heights in residential buildings and the 3D landscape patterns of residential areas, based on semantic three-dimensional grid data from a residential complex in Wuhan. The results indicate that (1) The characteristics of 3D landscape patterns vary across different regions within multi-unit high-rise residential areas. The landscape patches in the central and southern regions are more balanced compared to other areas, while there is minimal height variation in residential buildings in the northeastern region. (2) There are notable differences in comfort levels at varying heights across different areas of the residential district. In summer, residents expressing satisfaction with environmental comfort are primarily located in high-rise buildings in the central-southern region, whereas in winter, satisfaction is concentrated among residents in lower and mid-rise buildings in both the northern center and southern areas. (3) The degree of landscape fragmentation, the dominance of certain patches, and the distribution of buildings and vegetation at different heights significantly influence residents’ comfort. Achieving a balanced distribution of green spaces, reducing building density, and ensuring a uniform arrangement of trees of varied heights can effectively enhance the living environment for residents on lower floors, providing practical strategies for the planning of green spaces and built environments that improve overall resident quality of life. This research provides a theoretical foundation and reference for evaluating thermal comfort in high-rise residential areas and optimizing green space configurations.

Suggested Citation

  • Yaoyun Zhang & Ge Shi & Ziying Feng & Entao Zheng & Chuang Chen & Xinyu Li & Difan Yu & Yunpeng Zhang, 2025. "Study on the Relationship Between 3D Landscape Patterns and Residents’ Comfort in Urban Multi-Unit High-Rise Residential Areas: A Case Study of High-Density Inland City," Sustainability, MDPI, vol. 17(10), pages 1-32, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4347-:d:1653459
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4347/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/10/4347/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lili Zhang & Dong Wei & Yuyao Hou & Junfei Du & Zu’an Liu & Guomin Zhang & Long Shi, 2020. "Outdoor Thermal Comfort of Urban Park—A Case Study," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    2. Contesse, Maria & van Vliet, Bas J.M. & Lenhart, Jennifer, 2018. "Is urban agriculture urban green space? A comparison of policy arrangements for urban green space and urban agriculture in Santiago de Chile," Land Use Policy, Elsevier, vol. 71(C), pages 566-577.
    3. Hyomun Lee & Kyungwoo Lee & Eunho Kang & Dongsu Kim & Myunghwan Oh & Jongho Yoon, 2023. "Evaluation of Heated Window System to Enhance Indoor Thermal Comfort and Reduce Heating Demands Based on Simulation Analysis in South Korea," Energies, MDPI, vol. 16(3), pages 1-22, February.
    4. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
    5. Mehmet Cetin & Mehtap Ozenen Kavlak & Muzeyyen Anil Senyel Kurkcuoglu & Gulsah Bilge Ozturk & Saye Nihan Cabuk & Alper Cabuk, 2024. "Determination of land surface temperature and urban heat island effects with remote sensing capabilities: the case of Kayseri, Türkiye," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(6), pages 5509-5536, April.
    6. Ge Shi & Yutong Wang & Jingran Zhang & Jinghai Xu & Yu Chen & Wei Chen & Jiahang Liu, 2024. "Spatiotemporal Pattern Analysis and Prediction of Carbon Storage Based on Land Use and Cover Change: A Case Study of Jiangsu Coastal Cities in China," Land, MDPI, vol. 13(11), pages 1-22, October.
    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. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    2. Donghe Li & Xin Hu & John Rollo & Mark Luther & Min Lu & Chunlu Liu, 2025. "Spatial Cluster Characteristics of Land Surface Temperatures," Sustainability, MDPI, vol. 17(6), pages 1-24, March.
    3. Zhikun Ding & Rongsheng Liu & Zongjie Li & Cheng Fan, 2020. "A Thematic Network-Based Methodology for the Research Trend Identification in Building Energy Management," Energies, MDPI, vol. 13(18), pages 1-33, September.
    4. Yuan Ma & Heng Liang & Han Li & Yaping Liao, 2020. "Towards the Healthy Community: Residents’ Perceptions of Integrating Urban Agriculture into the Old Community Micro-Transformation in Guangzhou, China," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
    5. Lee, Chien-Chiang & Wang, Fuhao & Chang, Yu-Fang, 2023. "Towards net-zero emissions: Can green bond policy promote green innovation and green space?," Energy Economics, Elsevier, vol. 121(C).
    6. Yunpeng Sun & Ruoya Jia & Asif Razzaq & Qun Bao, 2023. "RETRACTED ARTICLE: Drivers of China’s geographical renewable energy development: evidence from spatial association network structure approaches," Economic Change and Restructuring, Springer, vol. 56(6), pages 4115-4163, December.
    7. Yuanfan Zheng & Liang Chen & Haipeng Zhao, 2024. "Assessing Building Energy Savings and the Greenhouse Gas Mitigation Potential of Green Roofs in Shanghai Using a GIS-Based Approach," Sustainability, MDPI, vol. 16(18), pages 1-23, September.
    8. Gabriele Battista & Emanuele de Lieto Vollaro & Andrea Vallati & Roberto de Lieto Vollaro, 2023. "Technical–Financial Feasibility Study of a Micro-Cogeneration System in the Buildings in Italy," Energies, MDPI, vol. 16(14), pages 1-15, July.
    9. Ana M. Bartolome & Deiyalí A. Carpio & Beatriz Urbano, 2022. "Urban Agriculture Digital Planning for the European Union’s Green Deal," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(59), pages 159-159.
    10. Francisco Estrada & Veronica Lupi & W. J. Wouter Botzen & Richard S. J. Tol, 2025. "Urban and non-urban contributions to the social cost of carbon," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    11. Sánchez-Guevara Sánchez, Carmen & Sanz Fernández, Ana & Núñez Peiró, Miguel & Gómez Muñoz, Gloria, 2020. "Energy poverty in Madrid: Data exploitation at the city and district level," Energy Policy, Elsevier, vol. 144(C).
    12. Shi, Luyang & Luo, Zhiwen & Matthews, Wendy & Wang, Zixuan & Li, Yuguo & Liu, Jing, 2019. "Impacts of urban microclimate on summertime sensible and latent energy demand for cooling in residential buildings of Hong Kong," Energy, Elsevier, vol. 189(C).
    13. Samuelson, Holly W. & Baniassadi, Amir & Gonzalez, Pablo Izaga, 2020. "Beyond energy savings: Investigating the co-benefits of heat resilient architecture," Energy, Elsevier, vol. 204(C).
    14. Coyne, Bryan & Denny, Eleanor, 2021. "Retrofit effectiveness: Evidence from a nationwide residential energy efficiency programme," Energy Policy, Elsevier, vol. 159(C).
    15. George M. Stavrakakis & Dimitris Al. Katsaprakakis & Markos Damasiotis, 2021. "Basic Principles, Most Common Computational Tools, and Capabilities for Building Energy and Urban Microclimate Simulations," Energies, MDPI, vol. 14(20), pages 1-41, October.
    16. Meng, Fanchao & Zhang, Lei & Ren, Guoyu & Zhang, Ruixue, 2023. "Impacts of UHI on variations in cooling loads in buildings during heatwaves: A case study of Beijing and Tianjin, China," Energy, Elsevier, vol. 273(C).
    17. Myungjin Kim & Li Wang & Yuyu Zhou, 2021. "Spatially Varying Coefficient Models with Sign Preservation of the Coefficient Functions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 367-386, September.
    18. Pigliautile, I. & Pisello, A.L. & Bou-Zeid, E., 2020. "Humans in the city: Representing outdoor thermal comfort in urban canopy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    19. Tian, Xiaoyu & Zhang, Hanwen & Liu, Lin & Huang, Jiahao & Liu, Liru & Liu, Jing, 2024. "Establishment of LCZ-based urban building energy consumption dataset in hot and humid subtropical regions through a bottom-up method," Applied Energy, Elsevier, vol. 368(C).
    20. Gabriele Battista & Emanuele de Lieto Vollaro & Luca Evangelisti & Roberto de Lieto Vollaro, 2022. "Urban Overheating Mitigation Strategies Opportunities: A Case Study of a Square in Rome (Italy)," Sustainability, MDPI, vol. 14(24), pages 1-18, December.

    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:10:p:4347-:d:1653459. 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.