Early Warning of the Carbon-Neutral Pressure Caused by Urban Agglomeration Growth: Evidence from an Urban Network-Based Cellular Automata Model in the Greater Bay Area
文献类型：期刊论文
| 作者 | He, Sanwei5; Ma, Shifa4; Zhang, Bin3; Li, Guangdong2; Yang, Zhenjie1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:2页码:21 |
| 关键词 | carbon neutrality cellular automata urban growth land use urban agglomeration |
| DOI | 10.3390/rs15020338 |
| 通讯作者 | Zhang, Bin(zhangb@cug.edu.cn) |
| 英文摘要 | Carbon neutrality is becoming an important development goal for regions and countries around the world. Land-use cover/change (LUCC), especially urban growth, as a major source of carbon emissions, has been extensively studied to support carbon-neutral planning. However, studies have typically used methods of small-scale urban growth simulation to model urban agglomeration growth to assist in carbon-neutral planning, ignoring the significant characteristics of the process to achieve carbon neutrality: large-scale and long-term. This paper proposes a framework to model large-scale and long-term urban growth, which couples a quantity module and a spatial module to model the quantity and spatial allocation of urban land, respectively. This framework integrates the inertia of historical land-use change, the driving effects of the urbanization law (S-curve), and the traction of the urban agglomeration network to model the long-term quantity change of urban land. Moreover, it couples a partitioned modeling framework, spatially heterogeneous rules derived by geographically weighted regression (GWR), and quantified land-use planning orientations to build a cellular automata (CA) model to accurately allocate the urbanized cells in a large-scale spatial domain. Taking the Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA) as an example, the proposed framework is calibrated by the urban growth from 2000 to 2010 and validated by that from 2010 to 2020. The figure of merit (FoM) of the results simulated by the framework is 0.2926, and the simulated results are also assessed by some evidence, which both confirm the good performance of the framework to model large-scale and long-term urban growth. Coupling with the coefficients proposed by the Intergovernmental Panel on Climate Change (IPCC), this framework is used to project the carbon emissions caused by urban growth in the GHMGBA from 2020 to 2050. The results indicate that Guangzhou, Foshan, Huizhou, and Jiangmen are under great pressure to achieve the carbon-neutral targets in the future, while Hong Kong, Macao, Shenzhen, and Zhuhai are relatively easy to bring up to the standard. This research contributes to the ability of land-use models to simulate large-scale and long-term urban growth to predict carbon emissions and to support the carbon-neutral planning of the GHMGBA. |
| WOS关键词 | LAND-USE CHANGE ; GRAVITATIONAL-FIELD MODEL ; CLIMATE-CHANGE ; COVER CHANGE ; ECONOMIC-GROWTH ; SIMULATION ; EXPANSION ; IMPACT ; URBANIZATION ; NEIGHBORHOOD |
| 资助项目 | National Natural Science Foundation of China[41971207] ; National Natural Science Foundation of China[42071207] ; National Natural Science Foundation of China[41901311] ; Fundamental Research Funds for the Central Universities ; Zhongnan University of Economics and Law[2722022BY018] ; CUG Scholar Scientific Research Funds at China University of Geosciences (Wuhan)[2022129] ; Macao Polytechnic University[RP/ESCHS-01/2021] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000927708600001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Zhongnan University of Economics and Law ; CUG Scholar Scientific Research Funds at China University of Geosciences (Wuhan) ; Macao Polytechnic University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/190032]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Bin |
| 作者单位 | 1.Macao Polytech Univ, Fac Humanities & Social Sci, Macau 999078, Macao, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.China Univ Geosci, Sch Publ Adm, Wuhan 430074, Peoples R China 4.Guangdong Univ Technol, Sch Architecture & Urban Planning, Guangzhou 510090, Peoples R China 5.Zhongnan Univ Econ & Law, Sch Publ Adm, Wuhan 430073, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Sanwei,Ma, Shifa,Zhang, Bin,et al. Early Warning of the Carbon-Neutral Pressure Caused by Urban Agglomeration Growth: Evidence from an Urban Network-Based Cellular Automata Model in the Greater Bay Area[J]. REMOTE SENSING,2023,15(2):21. |
| APA | He, Sanwei,Ma, Shifa,Zhang, Bin,Li, Guangdong,&Yang, Zhenjie.(2023).Early Warning of the Carbon-Neutral Pressure Caused by Urban Agglomeration Growth: Evidence from an Urban Network-Based Cellular Automata Model in the Greater Bay Area.REMOTE SENSING,15(2),21. |
| MLA | He, Sanwei,et al."Early Warning of the Carbon-Neutral Pressure Caused by Urban Agglomeration Growth: Evidence from an Urban Network-Based Cellular Automata Model in the Greater Bay Area".REMOTE SENSING 15.2(2023):21. |
入库方式： OAI收割
来源：地理科学与资源研究所
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