Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China
文献类型：期刊论文
| 作者 | Lu, Lu1; Xue, Qiang1; Zhang, Xiaojing1; Qin, Changbo1; Jia, Lizhi2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 15期号:18页码:23 |
| 关键词 | Markov-FLUS-InVEST model carbon storage multi-scenario simulation OPGD model quantitative attribution |
| DOI | 10.3390/rs15184472 |
| 通讯作者 | Qin, Changbo(qincb@caep.org.cn) |
| 英文摘要 | Rapidly predicting and revealing the spatiotemporal characteristics and driving factors of land-use changes in carbon storage within megacities under different scenarios is crucial to achieving sustainable development. In this study, Jinan City (JNC) is taken as the study area, and the Markov-FLUS-InVEST model is utilized to predict and analyze the spatiotemporal variation in carbon storage in 2030 under three scenarios, namely, the natural development scenario (S1), the ecological conservation scenario (S2), and the economic development scenario (S3). The drivers of carbon storage changes were identified using an optimal parameter-based geographic detection (OPGD) model. The findings indicate that (1) land use from 2010 to 2018 shows a trend of continuous expansion of construction land and reduction in arable land. (2) The main types of carbon pools were cropland, forest, and grassland, accounting for more than 96% of the total amount. Carbon storage showed a decreasing trend from 2010 to 2018, and the main type of carbon pool that decreased was cropland. The center of gravity of carbon storage increases and decreases was located in the southern Lixia District, and the center of gravity of increase and decrease moved to the southwest by 3057.48 m and 1478.57 m, respectively. (3) From 2018 to 2030, the reductions in carbon stocks were 3.20 x 106 t (S1), 2.60 x 106 t (S2), and 4.26 x 106 t (S3), and the carbon release was about 9 times (S1), 4 times (S2), and 10 times (S3) that of the carbon sink. (4) The contribution of slope (A2) boolean AND nighttime light index (B6) and elevation (A1) boolean AND nighttime light index (B6) to the regional heterogeneity of carbon stocks was the largest among the interaction drivers. To sum up, this study deepens the simulation of spatial and temporal dynamics of carbon storage under land-use changes in megacities and the related driving mechanism, which can provide the basis for scientific decision-making for cities to conduct territorial spatial planning and ecological protection and restoration. |
| WOS关键词 | LAND-USE CHANGE ; CA-MARKOV ; SEQUESTRATION ; SERVICES ; FLUS |
| 资助项目 | I am grateful for this study to be supported by the Tsien Hsue-Shen Urbanology Award of Hangzhou International Urbanology Research Center and Zhejiang Urban Governance Studies Center, and we also appreciate the reviewers for providing valuable comments. ; Tsien Hsue-Shen Urbanology Award of Hangzhou International Urbanology Research Center ; Zhejiang Urban Governance Studies Center |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:001075854100001 |
| 资助机构 | I am grateful for this study to be supported by the Tsien Hsue-Shen Urbanology Award of Hangzhou International Urbanology Research Center and Zhejiang Urban Governance Studies Center, and we also appreciate the reviewers for providing valuable comments. ; Tsien Hsue-Shen Urbanology Award of Hangzhou International Urbanology Research Center ; Zhejiang Urban Governance Studies Center |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/198379]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Qin, Changbo |
| 作者单位 | 1.Chinese Acad Environm Planning, Inst Strateg Planning, Beijing 100041, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Lhasa Plateau Ecosyst Res Stn, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Lu,Xue, Qiang,Zhang, Xiaojing,et al. Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China[J]. REMOTE SENSING,2023,15(18):23. |
| APA | Lu, Lu,Xue, Qiang,Zhang, Xiaojing,Qin, Changbo,&Jia, Lizhi.(2023).Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China.REMOTE SENSING,15(18),23. |
| MLA | Lu, Lu,et al."Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China".REMOTE SENSING 15.18(2023):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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