Detecting the slope movement after the 2018 Baige Landslides based on ground-based and space-borne radar observations

Li, Yongsheng; Jiao, Qisong; Hu, Xiuhong; Li, Zong-Liang; Li, Bingquan; Zhang, Jingfa; Jiang, Wenliang; Luo, Yuan; Li, Qiang; Ren-ji, BA

doi:10.1016/j.jag.2019.101949

Cited by 39 publications

(15 citation statements)

References 38 publications

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“…It also resulted in large-scale casualties and property losses upstream and downstream [22,23]. In 2018, a large-scale high-level rock landslide occurred in Baige Village, which caused a break in the Jinsha River for 2 days [24]. The economic loss caused by this landslide amounted to CNY 15 billion.…”

Section: Study Areamentioning

confidence: 99%

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

et al. 2021

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Construction of the 998.64-km Linzhi–Ya’an section of the Sichuan‒Tibet Railway has been influenced by landslide disasters, threatening the safety of Sichuan‒Tibet railway projects. Landslide identification and deformation analysis in this area are urgently needed. In this context, it was the first time that 164 advanced land-observing satellite-2 (ALOS-2) phased array type L-band synthetic aperture radar-2 (PALSAR-2) images were collected to detect landslide disasters along the entire Linzhi‒Ya’an section. Interferogram stacking and small baseline interferometry methods were used to derive the deformation rate and time-series deformation from 2014‒2020. After that, the hot spot analysis method was introduced to conduct spatial clustering analysis of the annual deformation rate, and the effective deformation area was quickly extracted. Finally, 517 landslide disasters along the Linzhi‒Ya’an route were detected by integrating observed deformation, Google Earth optical images, and external geological data. The main factors controlling the spatial landslide distribution were analyzed. In the vertical direction, the spatial landslide distribution was mainly concentrated in the elevation range of 3000‒5000 m, the slope range of 10‒40°, and the aspect of northeast and east. In the horizontal direction, landslides were concentrated near rivers, and were also closely related to earthquake-prone areas, fault zones, and high-precipitation areas. In short, rainfall, freeze–thaw weathering, seismic activity, and fault zones are the main factors inducing landslides along this route. This research provides scientific support for the construction and operation of the Linzhi‒Ya’an section of the Sichuan‒Tibet Railway.

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Section: Study Areamentioning

confidence: 99%

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

et al. 2021

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“…In the deformation velocity map shown in Figure 8, we can still see some incoherence effects. To reduce incoherence and atmospheric influences, the data acquisition frequency can be further improved (Li et al 2020). Due to the impact of the radar having a single observation angle, it is impossible to fully observe the deformation features.…”

Section: Post-disaster Emergency Analysismentioning

confidence: 99%

Analyzing the formation mechanism of the Xuyong landslide, Sichuan province, China, and emergency monitoring based on multiple remote sensing platform techniques

Jiang

Jiao

et al. 2020

Geomatics, Natural Hazards and Risk

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In this study, multitemporal satellite images, unmanned aerial vehicle (UAV) photogrammetry and ground-based radar were utilized to investigate the formation mechanism and disaster features of different phases of the Xuyong landslide disaster that occurred in Sichuan Province on December 9, 2018. Field survey indicates that the estimated landslide volume is approximately 35000 m 3 . The landslide is a typical dualistic soil-rock structural landslide with bedding planes. The sliding surface is located in a thin layer of limestone which is characterized by the X-shaped conjugate joint planes. The steep slope has been cut and transformed by human disturbances, which have influenced the slope stability and the drainage of precipitation along the slope. Many factors, including the regional geological structure, stratum lithology, slope topography, landform morphology, and precipitation, have contributed to the Xuyong landslide during the pre-disaster phase. Post-disaster emergency observation revealed that subsequent deformation was located mainly along the back edge of the landslide, where the maximum surficial deformation reached only 18 mm/day over a small area, reflecting the low probability of a secondary landslide hazard. Our research provides significant guidelines for investigating potential landslide dangers in similar environments and for post-disaster emergency response using multiple remote sensing (RS) platforms.

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“…where Θ −3dB is the half power wave velocity width and R is the azimuth distance. The azimuth resolution is 6.28 m (1 km), and the range resolution is 0.75 m [57]. Processing of GPRI-II raw data to single look complex (SLC) images is implemented within the software produced by the developer.…”

Section: Data Analysis and Interpretationmentioning

confidence: 99%

Real-Time Diagnosis of Island Landslides Based on GB-RAR

Cai

et al. 2020

JMSE

Self Cite

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Landslides are one of the most frequent and serious geological disasters that threaten people’s lives and property safety. In recent years, with the rapid development of the coastal economy and the increasingly strained spatial resources, the island development activities have become extremely rapid, resulting in the frequent occurrence of landslides on the island. We selected Beichangshan Island in the north of China as the research area. By using high-precision ground-based real aperture radar (GB-RAR) measurement technology, the displacement changes of potential landslides are monitored continuously and dynamically to realize the real-time diagnosis and early warning of island landslides. At the same time, the data interpretation method and key processing flow are described in detail. The results show that during the whole monitoring process, an area of obvious change is found, which is mainly located in the middle of the landslide mass. The mean velocity rate shows a nonlinear deformation trend. The maximum deformation of the landslide in the five selected points reaches 4.5 mm, which indicates that the area is in an unstable stage. The deformation monitoring ability of GB-RAR technology to identify the sub-millimeter level is demonstrated, and the monitoring method is verified. The validity and reliability of the method can be applied to real-time dynamic fine deformation diagnosis of island landslides. Its accuracy can meet the needs of dynamic change monitoring of island landslides, and it can become an important tool and means for early warning and treatment of landslides. The research is conducive to further enriching and improving the monitoring method system of island geological disasters in China, provides a scientific basis and technical support for early warning and disaster prevention and mitigation of island landslides, and can be popularized and applied in the monitoring of island landslides.

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Detecting the slope movement after the 2018 Baige Landslides based on ground-based and space-borne radar observations

Cited by 39 publications

References 38 publications

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

Analyzing the formation mechanism of the Xuyong landslide, Sichuan province, China, and emergency monitoring based on multiple remote sensing platform techniques

Real-Time Diagnosis of Island Landslides Based on GB-RAR

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