Evaluating the Multidimensional Stability of Regional Ecosystems Using the LandTrendr Algorithm
文献类型：期刊论文
| 作者 | Li, Lijuan1,3; Du, Jiaqiang1,3; Wu, Jin2; Sheng, Zhilu1,3; Zhu, Xiaoqian1,3; Song, Zebang1,3; Zhai, Guangqing1,3; Chong, Fangfang1,3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2024-10-01 |
| 卷号 | 16期号:20页码:20 |
| 关键词 | stability multidimensionality disturbance LandTrendr lower reaches of the Yellow River Basin |
| DOI | 10.3390/rs16203762 |
| 通讯作者 | Du, Jiaqiang(dujq@craes.org.cn) |
| 英文摘要 | Stability is a key characteristic for understanding ecosystem processes and evolution. However, research on the stability of complex ecosystems often faces limitations, such as reliance on single parameters and insufficient representation of continuous changes. This study developed a multidimensional stability assessment system for regional ecosystems based on disturbances. Focusing on the lower reaches of the Yellow River Basin (LR-YRB), we integrated the remote sensing ecological index (RSEI) with texture structural parameters, and applied the Landsat-based detection of trends in disturbance and recovery (LandTrendr) algorithm to analyze the continuous changes in disturbances and recovery from 1986 to 2021, facilitating the quantification and evaluation of resistance, resilience, and temporal stability. The results showed that 72.27% of the pixels experienced 1-9 disturbances, indicating the region's sensitivity to external factors. The maximum disturbances primarily lasted 2-3 years, with resistance and resilience displaying inverse spatial patterns. Over the 35-year period, 61.01% of the pixels exhibited moderate temporal stability. Approximately 59.83% of the pixels recovered or improved upon returning to pre-disturbance conditions after maximum disturbances, suggesting a strong recovery capability. The correlation among stability dimensions was low and influenced by disturbance intensity, underscoring the necessity for a multidimensional assessment of regional ecosystem stability based on satellite remote sensing. |
| WOS关键词 | LANDSAT TIME-SERIES ; FOREST CHANGE ; DISTURBANCE ; TRANSFORMATION ; ATTRIBUTION ; POPULATION ; GRASSLANDS ; DYNAMICS ; RECOVERY ; TRENDS |
| 资助项目 | Fundamental Research Funds for the Central Public-interest Scientific Institution ; National Natural Science Foundation of China[41001055] ; [2024YSKY-37] ; [2022YSKY-17] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001341719500001 |
| 出版者 | MDPI |
| 资助机构 | Fundamental Research Funds for the Central Public-interest Scientific Institution ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/209863]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Du, Jiaqiang |
| 作者单位 | 1.Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Chinese Res Inst Environm Sci, State Environm Protect Key Lab Reg Ecoproc & Funct, Beijing 100012, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Lijuan,Du, Jiaqiang,Wu, Jin,et al. Evaluating the Multidimensional Stability of Regional Ecosystems Using the LandTrendr Algorithm[J]. REMOTE SENSING,2024,16(20):20. |
| APA | Li, Lijuan.,Du, Jiaqiang.,Wu, Jin.,Sheng, Zhilu.,Zhu, Xiaoqian.,...&Chong, Fangfang.(2024).Evaluating the Multidimensional Stability of Regional Ecosystems Using the LandTrendr Algorithm.REMOTE SENSING,16(20),20. |
| MLA | Li, Lijuan,et al."Evaluating the Multidimensional Stability of Regional Ecosystems Using the LandTrendr Algorithm".REMOTE SENSING 16.20(2024):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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