Remote Sensing Precursors Analysis for Giant Landslides
文献类型：期刊论文
| 作者 | Lan, Hengxing1,2; Liu, Xiao2,3; Li, Langping2; Li, Quanwen2; Tian, Naiman2,3; Peng, Jianbing1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-09-01 |
| 卷号 | 14期号:17页码:28 |
| 关键词 | giant landslide remote sensing technology precursor analysis geomorphological precursors geotechnical precursors geoenvironmental precursors |
| DOI | 10.3390/rs14174399 |
| 通讯作者 | Lan, Hengxing(lanhx@lreis.ac.cn) |
| 英文摘要 | Monitoring and early warning systems for landslides are urgently needed worldwide to effectively reduce the losses of life and property caused by these natural disasters. Detecting the precursors of giant landslides constitutes the premise of landslide monitoring and early warning, and remote sensing is a powerful means to achieve this goal. In this work, we aim to summarize the basic types and evolutionary principles of giant landslide precursors, describe the remote sensing methods capable of identifying those precursors, and present typical cases of related sliding. Based on a review of the literature and an analysis of remote sensing imagery, the three main types of remote sensing techniques for capturing the geomorphological, geotechnical, and geoenvironmental precursors of giant landslides are optical, synthetic aperture radar (SAR), and thermal infrared methods, respectively. Time-series optical remote sensing data from medium-resolution satellites can be used to obtain abundant information on geomorphological changes, such as the extension of cracks and erosion ditches, and band algebraic analysis, image enhancement, and segmentation techniques are valuable for focusing on the locations of geomorphological landslide precursors. SAR sensors have the ability to monitor the slight slope deformation caused by unfavorable geological structures and can provide precursor information on imminent failure several days before a landslide; furthermore, persistent scatterer interferometric SAR has significant advantages in large-scale surface displacement monitoring. Thermal infrared imagery can identify landslide precursors by monitoring geoenvironmental information, especially in permafrost regions where glaciers are widely distributed; the reason may be that freeze-thaw cycles and snowmelt caused by increased temperatures affect the stability of the surface. Optical, SAR, and thermal remote sensing all exhibit unique advantages and play an essential role in the identification of giant landslide precursors. The combined application of these three remote sensing technologies to obtain the synthetic geomorphological, geotechnical, and geoenvironmental precursors of giant landslides would greatly promote the development of landslide early warning systems. |
| WOS关键词 | LANDSAT TIME-SERIES ; MEAGER VOLCANIC COMPLEX ; BRITISH-COLUMBIA ; JINSHA RIVER ; DETECTING PRECURSORS ; PERMANENT SCATTERERS ; MAOXIAN LANDSLIDE ; DEBRIS AVALANCHE ; TIBETAN PLATEAU ; PORE-PRESSURE |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23090301] ; Second Tibetan Plateau Scientific Expedition and Research (STEP) program[2019QZKK0904] ; National Natural Science Foundation of China[41941019] ; National Natural Science Foundation of China[42177150] ; Fundamental Research Funds for the Central Universities, CHD[300102262901] |
| 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:000851866900001 |
| 资助机构 | Strategic Priority Research Program of the Chinese Academy of Sciences ; Second Tibetan Plateau Scientific Expedition and Research (STEP) program ; National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities, CHD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/182873]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lan, Hengxing |
| 作者单位 | 1.Changan Univ, Sch Geol Engn & Geomat, Xian 710064, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lan, Hengxing,Liu, Xiao,Li, Langping,et al. Remote Sensing Precursors Analysis for Giant Landslides[J]. REMOTE SENSING,2022,14(17):28. |
| APA | Lan, Hengxing,Liu, Xiao,Li, Langping,Li, Quanwen,Tian, Naiman,&Peng, Jianbing.(2022).Remote Sensing Precursors Analysis for Giant Landslides.REMOTE SENSING,14(17),28. |
| MLA | Lan, Hengxing,et al."Remote Sensing Precursors Analysis for Giant Landslides".REMOTE SENSING 14.17(2022):28. |
入库方式： OAI收割
来源：地理科学与资源研究所
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