Slope Stability Hazard Assessment Using 3D Remote Sensing and Field Sketching Techniques Along Sohag-Red Sea-Cairo Highway, Egypt

El-Haddad, Bosy A.; Youssef, Ahmed M.; El-Shater, Abdel-Hamid; El-Khashab, Mohamed H.

doi:10.1007/978-3-319-53498-5_47

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…The Jinsha River is the third longest river in the world [12], and it flows through different topographical and geological structures, and the meteorology changes along its length. The river flows within deep canyon areas and plateaus [13,14], and the maximum height difference between canyons ranges from 2000-3000 m. The river valley is deeply incised, and the slopes of both banks are steep; it can thus easily become unstable under the actions of unloading, gravity, rainfall, and river erosion due to the influences of various factors, such as topography, stratum lithology, and geological structures [15,16]. In addition, the impoundment of reservoirs in canyons can aggravate the destruction of bank slopes [17,18].…”

Section: Introductionmentioning

confidence: 99%

Identification and Analysis of Landslides in the Ahai Reservoir Area of the Jinsha River Basin Using a Combination of DS-InSAR, Optical Images, and Field Surveys

Zuo

Da-ming

et al. 2022

Remote Sensing

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We employed ascending and descending Sentinel-1A, optical image data, and field investigation methods to identify and monitor landslides in the Jinsha River Basin to overcome the difficulties associated with the use of a single method and its inaccuracies in identifying landslides in the alpine and canyon areas. Using distributed scatterer-synthetic aperture radar interferometry (DS-InSAR), Sentinel-1A ascending and descending data were integrated to obtain surface deformation information within the study area from July 2017 to May 2019. Thereafter, high-resolution optical image data were introduced to interpret landslides, and field investigations were conducted to validate landslides. These combined methods enabled the assessment of spatiotemporal evolutionary characteristics, and their accuracy in identifying typical landslides was verified. The results showed that the use of both ascending and descending data effectively avoided certain problems, such as the inability to identify certain landslide hazards or the retrieval of incomplete identification results due to geometric distortion associated with single-track SAR imaging. The combined use of these methods effectively improves the timeliness and verification of the accuracy of landslides. Fifteen landslides were identified in the study area, which had different degrees of tension cracks, vertical dislocations, and slip marks that were verified in the field. Of these, two landslides show serious deformation characteristics that currently pose a serious threat to lives and infrastructure. Follow-up monitoring of these landslides is essential. These findings will assist in obtaining comprehensive information about the distribution of landslides and their deformation developmental trends in the Ahai Reservoir area of the Jinsha River Basin and show that the combined methods can be employed to prevent and control landslides in this area.

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