Exploring the Impact of Multitemporal DEM Data on the Susceptibility Mapping of Landslides
Exploring the Impact of Multitemporal DEM Data on the Susceptibility Mapping of Landslides
复制标题
探索多时相 DEM 数据对滑坡敏感性绘图的影响
DOI：
10.3390/app10072518
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发表时间：
2020-04
影响因子：
2.7
通讯作者：
Chen Guangqi
中科院分区：
文献类型：
--
作者：
Li Jiaying;Wang Weidong;Han Zheng;Li Yange;Chen Guangqi
数字高程模型(DEM)是滑坡易感性评价的基础数据模型。由于景观变化和重塑过程，DEM会表现出明显的时间变化，并对评估结果产生重大影响。为探讨数字高程模型时间变化对灾害易感性的影响，选取川南中国地区为研究区域。收集了17年来的多时相DEM数据，研究了该地区景观的地形变化。随后使用被广泛接受的Logistic回归模型(LRM)生成了滑坡的多时相易感地图。定量验证了前人研究支持的地形变化与滑坡易感性之间的正相关性。引入滑坡数量与发生灾害的易感水平区(RNA)的比值。核糖核酸显示，从2000年到2009年，敏感性水平普遍下降，而下降水平的比率比上升水平的比率大15倍以上。多时相数字高程模型对磁化率制图的影响是显著的。因此，敏感性评估应在研究时使用DEM数据。
Digital elevation models (DEMs) are fundamental data models used for susceptibility assessment of landslides. Due to landscape change and reshaping processes, a DEM can show obvious temporal variation and has a significant influence on assessment results. To explore the impact of DEM temporal variation on hazard susceptibility, the southern area of Sichuan province in China is selected as a study area. Multitemporal DEM data spanning over 17 years are collected and the topographic variation of the landscape in this area is investigated. Multitemporal susceptibility maps of landslides are subsequently generated using the widely accepted logistic regression model (LRM). A positive correlation between the topographic variation and landslide susceptibility that was supported by previous studies is quantitatively verified. The ratio of the number of landslides to the susceptibility level areas (RNA) in which the hazards occur is introduced. The RNA demonstrates a general decrease in the susceptibility level from 2000 to 2009, while the ratio of the decreased level is more than fifteen times greater than that of the ratio of the increased level. The impact of the multitemporal DEM on susceptibility mapping is demonstrated to be significant. As such, susceptibility assessments should use DEM data at the time of study.
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地震作用引发的区域海底滑坡敏感性评估
影响因子：
4.3
作者：
Nian Ting-kai;Guo Xing-sen;Zheng De-feng;Xiu Zong-xiang;Jiang Zheng-bo
通讯作者：
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DOI：
10.1016/j.scitotenv.2018.10.431
发表时间：
2019-02
期刊：
The Science of the total environment
影响因子：
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作者：
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通讯作者：
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影响因子：
3.9
作者：
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通讯作者：
Renske C. Terwisscha van Scheltinga;G. Coco;M. Kleinhans;H. Friedrich
影响因子：
7.4
作者：
Nikhil Nedumpallile Vasu;Seung-Rae Lee;A. Pradhan;Yun-Tae Kim;Sinhang Kang;Deuk-Hwan Lee
通讯作者：
Nikhil Nedumpallile Vasu;Seung-Rae Lee;A. Pradhan;Yun-Tae Kim;Sinhang Kang;Deuk-Hwan Lee
DOI：
10.1080/19475705.2019.1699606
发表时间：
2020-01
期刊：
Geomatics, Natural Hazards and Risk
影响因子：
--
作者：
Wei-dong Wang;Jiaying Li;Zheng Han
通讯作者：
Wei-dong Wang;Jiaying Li;Zheng Han