Role of geological structure in the occurrence of earthquake-induced landslides, the case of the 2007 Mid-Niigata Offshore Earthquake, Japan

Has, Baator; Nozaki, Tamotsu

doi:10.1016/j.enggeo.2014.09.006

Cited by 22 publications

(7 citation statements)

References 31 publications

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“…This area has a steep mountainous topography and conducive geology that makes it inclined to severe landsliding [23]. Extensive landslides in this area are reported after two major seismic events; Chuetsu earthquake in 2004 and Niigata Chuetsu-Oki earthquake in 2007 [35,36]. The heavy rainfall in summers, typhoons and snow melting brought occasional debris movement as well [37].…”

Section: Overview Of the Study Areamentioning

confidence: 99%

Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM

et al. 2019

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Landslides are typically triggered by earthquakes or rainfall occasionally a rainfall event followed by an earthquake or vice versa. Yet, most of the works presented in the past decade have been largely focused at the single event-susceptibility model. Such type of modeling is found insufficient in places where the triggering mechanism involves both factors such as one found in the Chuetsu region, Japan. Generally, a single event model provides only limited enlightenment of landslide spatial distribution and thus understate the potential combination-effect interrelation of earthquakes- and rainfall-triggered landslides. This study explores the both-effect of landslides triggered by Chuetsu-Niigata earthquake followed by a heavy rainfall event through examining multiple traditional statistical models and data mining for understanding the coupling effects. This paper aims to compare the abilities of the statistical probabilistic likelihood-frequency ratio (PLFR) model, information value (InV) method, certainty factors (CF), artificial neural network (ANN) and ensemble support vector machine (SVM) for the landslide susceptibility mapping (LSM) using high-resolution-light detection and ranging digital elevation model (LiDAR DEM). Firstly, the landslide inventory map including 8459 landslide polygons was compiled from multiple aerial photographs and satellite imageries. These datasets were then randomly split into two parts: 70% landslide polygons (5921) for training model and the remaining polygons for validation (2538). Next, seven causative factors were classified into three categories namely topographic factors, hydrological factors and geological factors. We then identified the associations between landslide occurrence and causative factors to produce LSM. Finally, the accuracies of five models were validated by the area under curves (AUC) method. The AUC values of five models vary from 0.77 to 0.87. Regarding the capability of performance, the proposed SVM is promising for constructing the regional landslide-prone potential areas using both types of landslides. Additionally, the result of our LSM can be applied for similar areas which have been experiencing both rainfall-earthquake landslides.

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Section: Overview Of the Study Areamentioning

confidence: 99%

Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM

et al. 2019

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“…Studies of the 1994 Northridge earthquake (M W = 6.7) in California (Parise and Jibson, 2000) and 2007 Mid-Niigata Offshore earthquake (M W = 6.8) in north-western Japan (Has and Nozaki, 2014) reported no significant relation between seismic wave propagation and landslide orientation in areas with low landslide ratio (< 2%), even though these areas had high PGA. Studies of the 1994 Northridge earthquake (M W = 6.7) in California (Parise and Jibson, 2000) and 2007 Mid-Niigata Offshore earthquake (M W = 6.8) in north-western Japan (Has and Nozaki, 2014) reported no significant relation between seismic wave propagation and landslide orientation in areas with low landslide ratio (< 2%), even though these areas had high PGA.…”

Section: Orientation Of Earthquake-triggered Landslidesmentioning

confidence: 99%

“…The earlier finding is supported by studies of earthquaketriggered landslides reported in other parts of the world. Studies of the 1994 Northridge earthquake (M W = 6.7) in California (Parise and Jibson, 2000) and 2007 Mid-Niigata Offshore earthquake (M W = 6.8) in north-western Japan (Has and Nozaki, 2014) reported no significant relation between seismic wave propagation and landslide orientation in areas with low landslide ratio (< 2%), even though these areas had high PGA. In contrast, studies of the 1993 earthquakes (M W = 6.7 and 6.9) in Finisterre Mountains, Papua New Guinea and the 2008 Wenchuan earthquake (M W = 7.9) in China (Xu et al, 2014) found significant relations in areas with high landslide ratio (≥ 2%).…”

Section: Orientation Of Earthquake-triggered Landslidesmentioning

confidence: 99%

“…Has and Nozaki, 2014;Kojima et al, 2015) so that landslide orientation can be similar to the dip direction of the bedding planes. Theoretically, rock materials tend to shear off the weak surface along discontinuity planes on the dip (cataclinal) slope (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Theoretically, rock materials tend to shear off the weak surface along discontinuity planes on the dip (cataclinal) slope (e.g. Has and Nozaki, 2014;Kojima et al, 2015) so that landslide orientation can be similar to the dip direction of the bedding planes. However, some studies (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Controls of preferential orientation of earthquake‐ and rainfall‐triggered landslides in Taiwan's orogenic mountain belt

Chen

Chang

Wang

et al. 2019

Earth Surf Processes Landf

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Landsliding usually occurs on specific hillslope aspect, which may reflect the control of specific geo‐environmental factors, triggering factors, or their interaction. To explore this notion, this study used island‐wide landslide inventories of the Chi‐Chi earthquake in 1999 (MW = 7.6) and Typhoon Morakot in 2009 in Taiwan to investigate the preferential orientation of landslides and the controls of landslide triggers and geological settings. The results showed two patterns. The orientations of earthquake‐triggered landslides were toward the aspect facing away from the epicenter in areas with peak ground acceleration (PGA) ≥ 0.6 g and landslide ratio ≥ 1%, suggesting that the orientations were controlled by seismic wave propagation. Rainfall‐triggered landslides tended to occur on dip slopes, instead of the windward slopes, suggesting that geological settings were a more effective control of the mass wasting processes on hillslope scale than the rainfall condition. This study highlights the importance of the endogenic processes, namely seismic wave and geological settings, on the predesigned orientation of landslides triggered by either earthquake or rainfall, which can in turn improve our knowledge of landscape evolution and landslide prediction. © 2019 John Wiley & Sons, Ltd.

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Rate Effect on the Residual Interface Strength Between two Different Soil Layers

Duong

Suzuki

2019

Lecture Notes in Civil Engineering

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Role of geological structure in the occurrence of earthquake-induced landslides, the case of the 2007 Mid-Niigata Offshore Earthquake, Japan

Cited by 22 publications

References 31 publications

Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM

Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM

Controls of preferential orientation of earthquake‐ and rainfall‐triggered landslides in Taiwan's orogenic mountain belt

Rate Effect on the Residual Interface Strength Between two Different Soil Layers

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