Abstract
The significance of land use in relation to carbon emissions cannot be overstated. Consequently, enhancing the structure of land use can concurrently decrease carbon emissions and improve land utilization efficiency. However, the majority of studies have primarily concentrated on static linear planning analysis, overlooking how land use spatial structure affects carbon emissions. There is still relatively limited research on the integrated simulation and optimization of land use, considering both low-carbon objectives and economic benefits. This study focuses on Changsha, simulating land use change and net carbon emissions coupling the SD (system dynamics) model with the FLUS (future land use simulation) model in three different scenarios, namely, Baseline Development (BD), Rapid Economic Development (RED), Coordinated Development (CD). The following are the key findings. Firstly, the integrated model demonstrates precision in predicting land use demands, patterns, and net carbon emissions. Secondly, land use demands in three different scenarios have a similar changing tendency by 2030. Farmland, grassland, and water areas are decreasing, while forestland, unused land, and built-up land are expanding at different rates. The land use patterns in the CD scenario are the most desirable compare to the other scenarios. The growth rate of built-up land has slowed down and is distributed in a compact manner, while the growth of forest land is faster and has a contiguous layout. The overall degree of landscape fragmentation has decreased, and different land types are distributed in a more balanced manner. This has led to a gradual decrease in net carbon emissions after reaching a peak in 2021, with a reduction of 2.43 million tons compared to 2020. According to these findings, the government should adjust land use structure while optimizing the economic development model to minimize carbon emissions, which enables us to provide a planning strategy for land use and sustainable development of China's major cities.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Similar Papers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.