TitleEnhanced dynamic landslide hazard mapping using MT-InSAR method in the Three Gorges Reservoir Area
AuthorsZhou, Chao
Cao, Ying
Hu, Xie
Yin, Kunlong
Wang, Yue
Catani, Filippo
AffiliationChina Univ Geosci, Sch Geog & Informat Engn, Wuhan 430078, Peoples R China
Res Ctr Geohazard Monitoring & Warning Three Gorg, Chongqing 40400, Peoples R China
China Univ Geosci, Fac Engn, Wuhan 430074, Peoples R China
Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China
Univ Padua, Dept Geosci, Via Gradenigo 6, I-35131 Padua, Italy
KeywordsEXTREME LEARNING-MACHINE
SUPPORT VECTOR MACHINE
SUSCEPTIBILITY ASSESSMENT
LOGISTIC-REGRESSION
RANDOM FOREST
INTERFEROMETRY
DISPLACEMENT
INFORMATION
BASIN
GIS
Issue DateApr-2022
PublisherLANDSLIDES
AbstractLandslide hazard mapping is essential for disaster reduction and mitigation. The hazard map produced by the spatiotemporal probability analysis is usually static with false-negative and false-positive errors due to limited data resolution. Here we propose a new method to obtain dynamic landslide hazard maps over the Wushan section of the Three Gorges Reservoir Area by introducing the ground deformation measured by the spaceborne Copernicus Sentinel-1 synthetic aperture radar (SAR) imagery collected from 9/30/2016 to 9/13/2017. We first determine the spatial probability of landslide occurrence predicted by the support vector machine algorithm. We also conducted the statistical analysis on the temporal probability of landslide occurrence under various rainfall conditions (0, 0-50, 50-100, and> 100 mm for the antecedent 5-day total). We initialize a preliminary landslide hazard map by combining the spatial and temporal landslide probabilities. Meanwhile, the ground deformation velocities during the representative dry and wet seasons can be extracted from multi-temporal interferometric SAR (MT-InSAR). Thereafter, the landslide hazard map can be finalized by an empirical assessment matrix considering both the preliminary landslide hazard map and deformation velocities. Our results demonstrate that false-negative and false-positive errors in the landslide hazard map can be effectively reduced with the assistance of the deformation information. Our proposed method can be used to assess the dynamic landslide hazard at higher accuracy.
URIhttp://hdl.handle.net/20.500.11897/641954
ISSN1612-510X
DOI10.1007/s10346-021-01796-1
IndexedSCI(E)
Appears in Collections:城市与环境学院

Files in This Work
There are no files associated with this item.

Web of Science®



Checked on Last Week

Scopus®



Checked on Current Time

百度学术™



Checked on Current Time

Google Scholar™





License: See PKU IR operational policies.