The Trade-Off and Coordinated Management of Land Use Compactness and Urban Carbon Sink Ecosystems Towards Net-Zero Goals

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land–Climate Interactions".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 839

Editors


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Guest Editor
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: land cover and use change (LCLUC); terrestrial carbon cycle; carbon disturbance; socio-ecological consequence of LCLUC
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Guest Editor
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: land resource management; urban/rural sociology; remote sensing of global change and the carbon cycle

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Guest Editor
Department of Geography and Environmental Studies, Faculty of Biological Sciences, University of Chittagong, Chittagong 4331, Bangladesh
Interests: geoinformatics (GIS); cartography; geodesy; surveying
School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
Interests: geography; global change and the carbon cycle; environmental science; agricultural plant science

Special Issue Information

Dear Colleagues,

Urban land use compactness is a pivotal measure for improving land use efficiency and curbing unregulated urban sprawl, and urban carbon sink ecosystems act as an essential natural carrier for carbon sequestration and offsetting anthropogenic urban carbon emissions. Both serve as core pillars for global cities advancing toward net-zero carbon goals. While the importance of both has been widely recognized, the trade-off and synergy mechanisms between land use compactness and urban carbon sink ecosystems remain poorly understood. For example, how can we quantify the impacts of compact land development on the structure and function of urban carbon sink ecosystems? How can we coordinate the development objectives of compact land use and the protection of carbon sink ecological space? What kind of planning models and management strategies for the coordination of compactness and carbon sinks should be constructed to achieve net-zero carbon in urban land use? We are assembling this Special Issue to better answer these questions, aiming to systematically explore the coordinated management paths of land use compactness and urban carbon sink ecosystems for the attainment of net-zero goals, thus providing scientific support for the sustainable utilization of urban land.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights about the mutual feedback mechanisms between land use compactness and urban carbon sink ecosystems; quantify the trade-off and synergy relationships at different urban scales and development stages; and propose targeted coordinated management strategies and planning schemes for the dual goals of sustainable land use and net-zero carbon. This topic is highly consistent with Land’s core scope of land system science, sustainable land use, and urban land planning and also responds to the journal’s focus on societally relevant and innovative research on climate change and carbon neutrality.

This Special Issue will welcome manuscripts that link the following themes:

  • Quantitative analysis of land use compactness' impacts on urban carbon sink ecosystems;
  • Multi-scale coordinated planning of land compactness and carbon sink ecological space;
  • Synergistic management strategies for compact development and carbon sink conservation;
  • Green infrastructure planning and nature-based solutions for enhancing carbon sinks in compact urban environments;
  • Remote sensing and big-data-driven monitoring of intensive land use and carbon sink ecosystem dynamics;
  • Cross-city comparative studies on compactness-carbon sink relationships across different urbanization stages and developmental contexts;
  • Future scenario simulation and backcasting of land use pathways toward net-zero carbon through compactness-carbon sink coordination.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Li Wang
Dr. Shidong Liu
Prof. Dr. Biswajit Nath
Dr. Jie Zhang
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly 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 2600 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 use
  • urban planning
  • sustainability
  • carbon emissions
  • carbon source
  • carbon sink
  • net-zero goals

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Published Papers (1 paper)

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Research

28 pages, 12007 KB  
Article
Spatial Patterns of Energy-Related Carbon Emissions from Residential Land: A Hybrid Physics–Machine-Learning Study of Shenzhen
by Lingyun Yao, Yonglin Zhang, Xue Qiao, Ke Wang, Bo Huang, Zheng Niu and Li Wang
Land 2026, 15(5), 772; https://doi.org/10.3390/land15050772 - 30 Apr 2026
Viewed by 394
Abstract
Accurate estimation of residential building energy consumption and associated CO2 emissions is essential for refined urban carbon management. This study develops a hybrid framework that integrates physics-based simulation and machine learning to estimate residential building energy use and energy-related CO2 emissions [...] Read more.
Accurate estimation of residential building energy consumption and associated CO2 emissions is essential for refined urban carbon management. This study develops a hybrid framework that integrates physics-based simulation and machine learning to estimate residential building energy use and energy-related CO2 emissions in Shenzhen in 2020. Representative building archetypes were first simulated and then used to train machine-learning models for large-scale applications. Building-level energy estimates were further combined with a bottom-up inventory to generate high-spatiotemporal-resolution maps of residential CO2 emissions. The results show that: (1) the selected model achieved good accuracy and temporal robustness, with strong agreement between estimated and reference energy use at daily, monthly, and annual scales; (2) residential energy use was primarily driven by meteorological conditions, especially daily mean temperature and the duration of high-temperature conditions, and exhibited clear weekly and seasonal patterns, with higher values on weekends and in summer; (3) residential CO2 emissions in Shenzhen reflected the combined effects of scale and intensity, with Longgang and Bao’an contributing the largest total emissions, Self-built residential buildings contributing the largest aggregate emissions, and Old residential buildings showing the highest average emissions per building; (4) emissions were highly concentrated in a small number of high-emission buildings, which were more frequently distributed along road-adjacent block perimeters. Overall, the proposed framework improves the fine-scale characterization of residential building CO2 emissions and provides a useful basis for hotspot identification and targeted mitigation. Full article
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