IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i4p476-d1371485.html
   My bibliography  Save this article

Spatial–Temporal Pattern Analysis and Development Forecasting of Carbon Stock Based on Land Use Change Simulation: A Case Study of the Xiamen–Zhangzhou–Quanzhou Urban Agglomeration, China

Author

Listed:
  • Suiping Zeng

    (School of Architecture, Tianjin Chengjian University, Tianjin 300384, China)

  • Xinyao Liu

    (School of Architecture, Tianjin Chengjian University, Tianjin 300384, China)

  • Jian Tian

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Jian Zeng

    (School of Architecture, Tianjin University, Tianjin 300072, China)

Abstract

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence of land use changes are crucial to the scientific management of environmental resources and the optimization of land spatial layout. Taking the Xiamen–Zhangzhou–Quanzhou urban agglomeration in the southeastern coastal region of China as an example, based on seven land use types from 1990 to 2020, including cultivated land, woodland, and construction land, we quantitatively investigate the spatial–temporal patterns of carbon stock development and the spatial correlation of carbon stock distribution. Additionally, two scenarios for the development of urban and ecological priorities in 2060 are established to investigate the effects of land use changes on carbon stock. The results indicate that (1) the research area has formed a land use spatial pattern centered around urban construction in the eastern bay area, with the western forest area and coastal forest belt serving as ecological barriers. Carbon stock is influenced by land use type, and the distribution of total carbon stock exhibits a spatial aggregation phenomenon characterized by “low in the southeast, high in the north, and medium in the center”. (2) Distance of trunk and secondary roads, elevation, slope, watershed borders, population size, and gross domestic product (GDP) factors are the main drivers of the growth of land use types. The primary causes of the reduction in carbon stock are the widespread conversion of cultivated land, woodland, and grassland into construction land, as well as water and unused land. (3) In 2060, there will be a decrease of 41,712,443.35 Mg in the urban priority development scenario compared to 2020, and a decrease of 29,577,580.48 Mg in the ecological priority development scenario. The estimated carbon stock under the two scenarios varies by 12,134,862.88 Mg. The average carbon storage of Zhangpu County, Quangang County, and Jimei County is expected to rise by one level under the ecological protection scenario, indicating that the vast forest area can become a potential area to maintain carbon stock. It is crucial to encourage the coordinated development of peri-urban agroforestry and ecological barriers, as well as to establish a harmonious spatial pattern of land use and carbon stock at the scale of urban agglomerations.

Suggested Citation

  • Suiping Zeng & Xinyao Liu & Jian Tian & Jian Zeng, 2024. "Spatial–Temporal Pattern Analysis and Development Forecasting of Carbon Stock Based on Land Use Change Simulation: A Case Study of the Xiamen–Zhangzhou–Quanzhou Urban Agglomeration, China," Land, MDPI, vol. 13(4), pages 1-26, April.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:4:p:476-:d:1371485
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/4/476/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/13/4/476/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dong-Feng Ren & Ai-Hua Cao & Fei-Yue Wang, 2023. "Response and Multi-Scenario Prediction of Carbon Storage and Habitat Quality to Land Use in Liaoning Province, China," Sustainability, MDPI, vol. 15(5), pages 1-23, March.
    2. Xu, Jinghang & Guan, Yuru & Oldfield, Jonathan & Guan, Dabo & Shan, Yuli, 2024. "China carbon emission accounts 2020-2021," Applied Energy, Elsevier, vol. 360(C).
    3. Min Li & Peng Zheng & Wenbin Pan, 2022. "Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian," Sustainability, MDPI, vol. 14(5), pages 1-25, March.
    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. Shuyu Yang & Jiaju Lin & Xiongzhi Xue, 2024. "Climate Change May Increase the Impact of Coastal Flooding on Carbon Storage in China’s Coastal Terrestrial Ecosystems," Land, MDPI, vol. 13(11), pages 1-21, November.
    2. Gao, Jinshuang & Li, Sheng & Wu, Fan & Jiang, Long & Zhao, Yazhou & Zhang, Xuejun, 2024. "Study on efficient heating method by solar coupled air source heat pump system with phase change heat storage in severe cold region," Applied Energy, Elsevier, vol. 367(C).
    3. Hua Duan & Bin Li & Qi Wang, 2024. "Static High-Quality Development Efficiency and Its Dynamic Changes for China: A Non-Radial Directional Distance Function and a Metafrontier Non-Radial Malmquist Model," Mathematics, MDPI, vol. 12(15), pages 1-19, July.
    4. Peng Zheng & Lanting Jin & Yuxiao Huang & Wenbin Pan, 2024. "Spatial and Temporal Dynamic Evolution and Correlation of Ecological Quality and Ecosystem Service Value in Fujian Province," Sustainability, MDPI, vol. 16(12), pages 1-19, June.
    5. Yingchu Guo & Dawei Xu & Jia Xu & Ziyi Yang, 2024. "Multi-Scale Analysis of Spatial and Temporal Evolution of Ecosystem Health in the Harbin–Changchun Urban Agglomeration, China," Sustainability, MDPI, vol. 16(2), pages 1-31, January.
    6. Rujun Zhao & Hai Chen & Xiaoying Liang & Miaomiao Yang & Yuhe Ma & Wenjing Lu, 2024. "Exploring the Influence of Digital Economy Growth on Carbon Emission Intensity Through the Lens of Energy Consumption," Sustainability, MDPI, vol. 16(21), pages 1-19, October.
    7. Yanzhen Lin & Lei Chen & Ying Ma & Tingting Yang, 2024. "Analysis and Simulation of Land Use Changes and Their Impact on Carbon Stocks in the Haihe River Basin by Combining LSTM with the InVEST Model," Sustainability, MDPI, vol. 16(6), pages 1-15, March.
    8. He, Peiming & Tian, Xingyue & Zhang, Jiaming & Yu, Siyu & Li, Shiyu & Lin, Chuan & Chen, Litai & Qian, Lei, 2024. "Can the China–Europe Railway Express reduce carbon dioxide emissions? New mechanism of the manufacturing industry substitution effect," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 1384-1405.
    9. Li Ming & Jiang Chang & Cheng Li & Yedong Chen & Cankun Li, 2022. "Spatial-Temporal Patterns of Ecosystem Services Supply-Demand and Influencing Factors: A Case Study of Resource-Based Cities in the Yellow River Basin, China," IJERPH, MDPI, vol. 19(23), pages 1-22, December.
    10. Xiaoqiu Chen & Jinxiang Wang, 2024. "The Impact of Regional Carbon Emission Reduction on Corporate ESG Performance in China," Sustainability, MDPI, vol. 16(13), pages 1-28, July.

    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:jlands:v:13:y:2024:i:4:p:476-:d:1371485. 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.