Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine
文献类型：期刊论文
| 作者 | Zhao, Zhengyuan ; Li, Ting; Zhang, Yunlong; Lu, Da; Wang, Cong; Lu, Yihe; Wu, Xing
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| 刊名 | REMOTE SENSING
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| 出版日期 | 2022 |
| 卷号 | 14期号:20页码:5279-1-19 |
| 关键词 | ecological vulnerability spatiotemporal patterns driving factor Google Earth Engine Qinghai-Tibet Plateau |
| 英文摘要 | With the background of climate change and intensified human activities, environmental problems are becoming increasingly prominent on the Qinghai-Tibet Plateau (QTP). For the development of efficient environmental policies and protection measures, quick and accurate assessments of the spatiotemporal patterns in ecological vulnerability are crucial. Based on the Google Earth Engine (GEE) platform, we used Moderate Resolution Imaging Spectroradiometer (MODIS), Shuttle Radar Topography Mission (SRTM), and human footprint (HFP) datasets to analyze the spatiotemporal distributions and main driving factors of the remote sensing ecological vulnerability index (RSEVI) for the QTP. Moreover, spatial autocorrelation analysis and the standard deviational ellipse (SDE) were used to analyze the spatiotemporal characteristics. Our results showed that the RSEVI gradually increased from the southeast to the northwest of the QTP. From 2000 to 2018, the potential vulnerability area increased by 6.59 x 10(4) km(2), while the extreme vulnerability area decreased by 1.84 x 10(4) km(2). Moran's I value of the RSEVI was greater than 0 and increased, indicating that the aggregation degree was increasing. The gravity center was located in Nagqu, Tibet, and shifted to the northwest from 2000 to 2015 and to the southeast from 2015 to 2018. The SDE rotated in a counterclockwise direction. The three most important driving factors of ecological vulnerability were wetness, land surface temperature (LST), and the normalized difference vegetation index (NDVI), indicating that climate and vegetation were the dominant factors. Moreover, this study developed a promising method for the ecological vulnerability assessment of large-scale and long time series datasets, and it provides theoretical support for the ecological conservation and sustainable development of the QTP under global change. |
| 源URL | [https://ir.rcees.ac.cn/handle/311016/48433]  |
| 专题 | 生态环境研究中心_城市与区域生态国家重点实验室 |
| 作者单位 | 1.University of Chinese Academy of Sciences, CAS 2.Research Center for Eco-Environmental Sciences (RCEES) 3.Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Zhao, Zhengyuan,Li, Ting,Zhang, Yunlong,et al. Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine[J]. REMOTE SENSING,2022,14(20):5279-1-19. |
| APA | Zhao, Zhengyuan.,Li, Ting.,Zhang, Yunlong.,Lu, Da.,Wang, Cong.,...&Wu, Xing.(2022).Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine.REMOTE SENSING,14(20),5279-1-19. |
| MLA | Zhao, Zhengyuan,et al."Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine".REMOTE SENSING 14.20(2022):5279-1-19. |
入库方式： OAI收割
来源：生态环境研究中心
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