Remote sensing monitoring of the SDG indicator mountain green cover index in China from 2000 to 2022
文献类型:期刊论文
| 作者 | Bian, Jinhu1,3; Zhao, Jinping2,3; Li, Ainong1,3; Deng, Yi2,3; Lei, Guangbin1,3; Zhang, Zhengjian1,3; Nan, Xi1,3; Naboureh, Amin3 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
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| 出版日期 | 2025-09-01 |
| 卷号 | 143页码:16 |
| 关键词 | Sustainable development goals (SDGs) Land cover Spatiotemporal change |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2025.104852 |
| 英文摘要 | Mountains provide vital ecosystem services that support the livelihoods of billions of people worldwide, playing a crucial role in biodiversity conservation and climate regulation. The United Nations 2030 Agenda for Sustainable Development has established a specific target (SDG 15.4) dedicated to mountain protection. The Mountain Green Cover Index (MGCI) serves as a key indicator for assessing the health of mountain ecosystems. As the 2030 Agenda passes its midpoint, the mid-term assessment of the MGCI is essential for adjusting implementation strategies and ensuring the realization of the 2030 Agenda for the protection of mountain ecosystems. However, existing country-level MGCI values fail to account for the three-dimensional characteristics unique to mountains. Additionally, quantifying the detailed mechanisms of change and dynamics in highly heterogeneous mountain areas within countries remains challenging. In this study, we developed a highresolution grid-based MGCI model for China and estimated MGCI values from 2000 to 2022 using 30 m annual land cover data and the true surface area of mountains. We analyzed the spatiotemporal patterns of the MGCI and quantified the impacts of anthropogenic and natural factors on MGCI dynamics during the 2022 midterm assessment. The results show that from 2000 to 2022, China's overall MGCI increased from 78.15 % to 82.23 %, with an average annual growth rate of 0.18 %. Notably, 8.48 % of mountains experienced an MGCI increase within the (0, 0.5) range, while only 0.03 % of areas saw a decrease greater than 0.5, primarily concentrated on the Qinghai-Tibetan Plateau. Spatial pattern analysis revealed clear variations in MGCI along elevation and hydrothermal gradients. Driving factor analysis indicated that water-related variables explain MGCI spatial distribution more effectively than thermal conditions. Furthermore, the interaction between grazing intensity and water factors demonstrated a strong synergistic effect on MGCI distribution. This research enhances the understanding of MGCI dynamics and its driving factors in China's mountain ecosystems, offering valuable reference for the timely achievement of mountain sustainable development goals. |
| WOS关键词 | ELEVATION ; WORLD ; VULNERABILITY ; DATASETS |
| 资助项目 | National Key Research and Development Program of China[2020YFA0608702] ; National Natural Science Foundation project of China[42171382] ; National Natural Science Foundation project of China[W2412146] ; National Natural Science Foundation project of China[42571453] ; National Natural Science Foundation project of China[U23A2019] ; National Natural Science Foundation project of China[W2433109] ; Science and Technology Research Program of Institute of Mountain Hazards and Environment, Chinese Academy of Sciences[IMHE-CXTD-03] ; Chinese Academy of Sciences Light of West China Program ; Sichuan province key research and development project[2023YFWZ0007] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001575530000002 |
| 出版者 | ELSEVIER |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation project of China ; Science and Technology Research Program of Institute of Mountain Hazards and Environment, Chinese Academy of Sciences ; Chinese Academy of Sciences Light of West China Program ; Sichuan province key research and development project |
| 源URL | [http://ir.imde.ac.cn/handle/131551/59172] ![]() |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 通讯作者 | Li, Ainong |
| 作者单位 | 1.Wanglang Mt Remote Sensing Observat & Res Stn Sich, Mianyang 621000, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610213, Sichuan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bian, Jinhu,Zhao, Jinping,Li, Ainong,et al. Remote sensing monitoring of the SDG indicator mountain green cover index in China from 2000 to 2022[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2025,143:16. |
| APA | Bian, Jinhu.,Zhao, Jinping.,Li, Ainong.,Deng, Yi.,Lei, Guangbin.,...&Naboureh, Amin.(2025).Remote sensing monitoring of the SDG indicator mountain green cover index in China from 2000 to 2022.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,143,16. |
| MLA | Bian, Jinhu,et al."Remote sensing monitoring of the SDG indicator mountain green cover index in China from 2000 to 2022".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 143(2025):16. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
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