landslide morphology
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2020 ◽  
Vol 125 (12) ◽  
Author(s):  
Brandon C. Johnson ◽  
Michael M. Sori
Keyword(s):  

2020 ◽  
pp. 1-10
Author(s):  
Frédérique Tremblay-Auger ◽  
Ariane Locat ◽  
Serge Leroueil ◽  
Pascal Locat ◽  
Denis Demers ◽  
...  

On 9 November 2016, a landslide in sensitive glaciomarine sediments occurred on a terrace of the Champlain River near the municipality of Saint-Luc-de-Vincennes, Quebec. The particularity of this event is that there are evidences that the movement started as a flowslide and then finished as a spread. The landslide morphology comprises horsts and grabens typical of spreads and also a large quantity of remolded material that flowed out of a pear-shaped crater with a narrow bottleneck, typical of flowslides. The geotechnical investigation of this landslide was performed by the Ministère des Transports du Québec (MTQ) in collaboration with Université Laval, and consisted of light detection and ranging (LiDAR) surveys, drone photography, several boreholes, piezocone tests with pore pressure measurements (CPTUs), field vane tests, and piezometric monitoring. They were used to characterize the landslide, to determine the location of the failure surface, and also to acquire information on the properties of the clay deposit. A combined analysis of the debris and volume calculations was done to reconstruct the different phases of flowing and spreading and their relative chronologies.


2018 ◽  
Vol 18 (3) ◽  
pp. 709-727 ◽  
Author(s):  
Kuo-Jen Chang ◽  
Yu-Chang Chan ◽  
Rou-Fei Chen ◽  
Yu-Chung Hsieh

Abstract. Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne lidar, were used in this study to decipher the morphological features of obscure landslides in volcanic regions and how the observed features may be used for understanding landslide occurrence and potential hazard. A morphological reconstruction method was proposed to assess landslide morphology based on the dome-shaped topography of the volcanic edifice and the nature of its morphological evolution. Two large-scale landslides in the Tatun volcano group in northern Taiwan were targeted to more accurately characterize the landslide morphology through airborne lidar and UAS-derived digital terrain models and images. With the proposed reconstruction method, the depleted volume of the two landslides was estimated to be at least 820 ± 20  ×  106 m3. Normal faulting in the region likely played a role in triggering the two landslides, because there are extensive geological and historical records of an active normal fault in this region. The subsequent geomorphological evolution of the two landslides is thus inferred to account for the observed morphological and tectonic features that are indicative of resulting in large and life-threatening landslides, as characterized using the recent remote sensing techniques.


2017 ◽  
Author(s):  
Kuo-Jen Chang ◽  
Yu-Chang Chan ◽  
Rou-Fei Chen ◽  
Yu-Chung Hsieh

Abstract. Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne LiDAR, were used in this study to decipher the morphological features of obscure landslides in volcanic regions. A morphological reconstruction method was proposed to assess landslide morphology based on the dome-shaped topography of the volcanic edifice and the nature of its morphological evolution. Two large-scale landslides in the Tatun volcano group in Northern Taiwan were targeted to more accurately characterize the landslide morphology through airborne LiDAR and UAS-derived digital terrain models and images. With the proposed reconstruction method, the depleted volume of the two landslides was estimated to be at least 820 ± 20 × 106 m3, approximately six times higher than the reported largest landslide volume in Taiwan. Normal faulting in the region likely played a role in triggering the two landslides, because there are extensive geological and historical records of an active normal fault in this region. The subsequent geomorphological evolution of the two landslides is inferred to account for the observed morphological and tectonic features, as characterized using the remote sensing techniques.


Author(s):  
O. E. Mora ◽  
M. G. Lenzano ◽  
C. K. Toth ◽  
D. A. Grejner-Brzezinska

Spatial resolution plays an important role in remote sensing technology as it defines the smallest scale at which surface features may be extracted, identified, and mapped. Remote sensing technology has become a vital component in recent developments for landslide susceptibility mapping. The spatial resolution is essential, especially when landslides are small and the dimensions of slope failures vary. If the spatial resolution is relevant to the surface features found in the landslide morphology, it will help improve the extraction, identification and mapping of landslide surface features. Although, the spatial resolution is a well-known issue, few studies have demonstrated the potential effects it may have on small landslide susceptibility mapping. For these reasons, an evaluation to assess the impact of spatial resolution was performed using data acquired along a transportation corridor in Zanesville, Ohio. Using a landslide susceptibility mapping algorithm, landslide surface features were extracted and identified on a cell-by-cell basis from Digital Elevation Models (DEM) generated at 50, 100, 200 and 400 cm spatial resolution. The performance of the landslide surface feature extraction algorithm was then evaluated using an inventory map and a confusion matrix to assess the effects of spatial resolution. In addition to assessing the performance of the algorithm, we statistically analyzed the surface features and their relevant patterns. The results from this evaluation reveal patterns caused by the varying spatial resolution. From this study we can conclude that the spatial resolution has an effect on the accuracy and surface features extracted for small landslide susceptibility mapping, as the performance is dependent on the scale of the landslide morphology.


Geomorphology ◽  
2006 ◽  
Vol 73 (1-2) ◽  
pp. 131-148 ◽  
Author(s):  
Nancy F. Glenn ◽  
David R. Streutker ◽  
D. John Chadwick ◽  
Glenn D. Thackray ◽  
Stephen J. Dorsch

1982 ◽  
Vol 64 (3-4) ◽  
pp. 149-159 ◽  
Author(s):  
William Renwick ◽  
Robert Brumbaugh ◽  
Larry Loeher

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