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Sustainable Urban and Rural Land Planning and Utilization
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Sustainable Urban and Rural Land Planning and Utilization

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2935

Special Issue Editors

Dr. Jing Cheng

E-Mail Website
Guest Editor
College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China
Interests: urban planning; land use; data analysis
Dr. Shanshan Wu

E-Mail Website
Guest Editor
School of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215011, China
Interests: collaborative development of rail transit and commerce; vitality of public spaces; vitality of commercial spaces
Prof. Dr. Miaojuan Peng

E-Mail Website
Guest Editor
School of Mechanics and Engineering Science, Shanghai University, Shanghai 200044, China
Interests: mathematical model; numerical method; numerical simulation; finite element method; meshless method
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable urban and rural land planning and utilization are important for the overall well-being and development of a country. Effective land planning and utilization can help safeguard natural resources, protect ecosystems, and mitigate environmental degradation. In climate change mitigation, sustainable land planning plays a significant role by reducing greenhouse gas emissions through measures like compact urban development, promoting public transportation, and preserving carbon sinks such as forests and grasslands. By optimizing land use patterns, countries can utilize resources more efficiently, reducing waste and enhancing resource productivity. This includes promoting sustainable agricultural practices, minimizing land degradation, and encouraging the efficient use of water and energy resources. Sustainable land planning fosters equitable access to housing, infrastructure, and services for all segments of society, reducing disparities and promoting social cohesion. Well-planned urban and rural areas are essential for economic growth and prosperity. Sustainable land planning attracts investment, stimulates job creation, and enhances the competitiveness of industries by providing efficient infrastructure, a skilled workforce, and a high quality of life for residents. Countries with robust land planning frameworks are better equipped to withstand and recover from shocks such as natural disasters, economic downturns, and pandemics. By incorporating resilience measures into land use planning, countries can build stronger, more adaptive communities that can bounce back more quickly from crises. Sustainable land planning respects and preserves cultural heritage sites, historic landmarks, and traditional landscapes. It integrates cultural considerations into development plans, ensuring that communities' unique identities and traditions are valued and celebrated. Sustainable land planning takes a holistic, long-term approach to development, considering the needs of present and future generations. By balancing economic growth with social equity and environmental conservation, countries can create resilient, prosperous, and livable communities that endure for generations to come.

With the developments of data science and big data, the quantitative analysis of land use and planning has been paying more and more attentions. Statistical data analysis methods have been widely applied to analyze land use and urban planning problems, such as land planning, land leasing, land cover, land use dynamics, residential land, industry land, commercial land, urban transport, and the corresponding government behavior.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Mathematical modelling.
  • Data analysis methods.
  • Data Pre-Processing of urban and rural land planning and utilization.
  • Data system or platform of land planning and utilization.
  • Deep learning and neural networks and application in land use and planning.
  • Complex network of land planning and utilization.
  • Software or programming of numerical simulation and data analysis.
  • Application of data science in land use and planning.
  • The policy of urban and rural planning and utilization.
  • Future strategies of sustainable urban and rural land planning and utilization.

We look forward to receiving your contributions.

Dr. Jing Cheng
Dr. Shanshan Wu
Prof. Dr. Miaojuan Peng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land planning
  • land utilization
  • mathematical modelling
  • data analysis
  • complex network
  • deep learning
  • software
  • land policy

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Published Papers (2 papers)

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18 pages, 50233 KiB  
Article
Site Selection for Elderly Care Facilities in the Context of Big Data: A Case Study of Xi’an, China
by Huangling Gu, Ruiwu Shen, Qianqian Chen, Mingzhuo Duan and Xianchao Zhao
Sustainability 2025, 17(4), 1540; https://doi.org/10.3390/su17041540 - 13 Feb 2025
Cited by 1 | Viewed by 633
Abstract
The accelerated aging of China’s population has made the optimization of elderly care facility locations a critical priority. The field of big data presents innovative approaches for determining the optimal site selection for such facilities. This study uses Xi’an City, in Shaanxi Province, [...] Read more.
The accelerated aging of China’s population has made the optimization of elderly care facility locations a critical priority. The field of big data presents innovative approaches for determining the optimal site selection for such facilities. This study uses Xi’an City, in Shaanxi Province, China, as a case study to explore how big data and the ID3 decision tree model can enhance the optimization of elderly care service facility locations. The study begins with a comprehensive analysis of Xi’an’s aging demographics, focusing on the current aging trends and the distribution characteristics of existing elderly care facilities. Utilizing the Baidu Map API, the study collected Point of Interest (POI) data for Xi’an, which were spatially analyzed using ArcGIS 10.8 software to identify the distribution patterns of elderly care facilities and their relationships with other public amenities. The ID3 algorithm was then employed to construct a decision tree model to simulate and predict optimal sites for elderly care facilities in Xi’an. By classifying and filtering POI data and dividing Xi’an into 500 m × 500 m grid units, the model was trained and validated, achieving an accuracy of 85.8%. The findings suggest that suitable sites for elderly care facilities in Xi’an should prioritize proximity to government offices and medical institutions, which would better address the healthcare needs of the elderly population. The application of the ID3 algorithm in planning the locations of elderly care facilities helps mitigate human biases and provides valuable insights for the planning of other public amenities. Full article
(This article belongs to the Special Issue Sustainable Urban and Rural Land Planning and Utilization)
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30 pages, 14521 KiB  
Article
Sustainable Protection Strategies for Traditional Villages Based on a Socio-Ecological Systems Spatial Pattern Evaluation: A Case Study from Jinjiang River Basin in China
by Xue Jiang, Shuhan Man, Xianglong Zhu, Hongyu Zhao and Tianjiao Yan
Sustainability 2024, 16(17), 7700; https://doi.org/10.3390/su16177700 - 4 Sep 2024
Viewed by 1463
Abstract
Traditional villages have reached milestones in developing a living culture, politics, economy, and society, among other aspects, while acting as important carriers of agricultural culture formed by long-term interactions between humans and nature. Unfortunately, traditional villages could disappear with the advent of urbanization. [...] Read more.
Traditional villages have reached milestones in developing a living culture, politics, economy, and society, among other aspects, while acting as important carriers of agricultural culture formed by long-term interactions between humans and nature. Unfortunately, traditional villages could disappear with the advent of urbanization. Therefore, this study enhances the accuracy of traditional village classification protection work by examining traditional villages in the Jinjiang River Basin in Quanzhou, China. A spatial pattern is extracted for the socio-ecological systems (SES) prototype of traditional villages, and an SES classification protection system is constructed based on a prototype analysis. Given the evaluation results, a K-means cluster analysis is applied to establish the SES sustainability levels for six types of traditional villages. After adjusting the types according to the principles of sustainability, equilibrium, and individual cases, six SES system types are identified: SES decay and shrinkage (Type 1), SES fusion and development (Type 2), SES ecological decline (Type 3), SES social decline (Type 4), SES ecological conservation (Type 5), and SES extensive development (Type 6). This system provides a quantitative analysis method to classify and protect concentrated and contiguous traditional villages. It also helps facilitate a better understanding of local rural society, economy, and culture, especially a deeper understanding of the interactions between humans and the rural environment. Full article
(This article belongs to the Special Issue Sustainable Urban and Rural Land Planning and Utilization)
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