The role of topography in the scaling distribution of landslide areas: A cellular automata modeling approach

Liucci, Luisa; Melelli, Laura; Suteanu, Cristian; Ponziani, Francesco

doi:10.1016/j.geomorph.2017.04.017

Cited by 28 publications

(19 citation statements)

References 51 publications

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“…Landslides are common geological hazards caused by multiple factors including landform [1,2], geological evolution [3], groundwater [4], land use type [5], precipitation [6,7], irrigation [8], earthquake [9], engineering construction [10], and climate change [11][12][13]. To avoid casualties caused by landslides and guarantee the stable development of mountainous areas, it is critical to determine a control and prevention scheme for landslides in a region.…”

Section: Introductionmentioning

confidence: 99%

Landslide Susceptibility Modeling Using Integrated Ensemble Weights of Evidence with Logistic Regression and Random Forest Models

2019

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The main aim of this study was to compare the performances of the hybrid approaches of traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE-LR) and machine learning-based random forest (WoE-RF) for landslide susceptibility mapping. The performance of the three landslide models was validated with receiver operating characteristic (ROC) curves and area under the curve (AUC). The results showed that the areas under the curve obtained using the WoE, WoE-LR, and WoE-RF methods were 0.720, 0.773, and 0.802 for the training dataset, and were 0.695, 0.763, and 0.782 for the validation dataset, respectively. The results demonstrate the superiority of hybrid models and that the resultant maps would be useful for land use planning in landslide-prone areas.

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Section: Introductionmentioning

confidence: 99%

Landslide Susceptibility Modeling Using Integrated Ensemble Weights of Evidence with Logistic Regression and Random Forest Models

2019

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“…With an occupancy of 11% of the land by landslides, this moment magnitude does not appear to be extreme. As the model by Liucci et al (2017) suggested that the intensity of an event controls the probability distribution of landslide size, the strong seismic intensity and peak ground acceleration of the Hokkaido Eastern Iburi Earthquake probably contributed to producing high rollover, together with soil layers that were very sensitive to ground shaking and the topographic characteristics of the study area. Unfortunately, this study did not address this issue further because of the limited availability of detailed information about the intensity.…”

Section: (7)mentioning

confidence: 97%

Topographic effects on frequency-size distribution of landslides triggered by the Hokkaido Eastern Iburi Earthquake in 2018

Kasai

Yamada

2019

Earth Planets Space

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This study examined the frequency-size distribution of 6117 landslides spread over 440 km 2 in Iburi Subprefecture, Hokkaido, Japan, induced by the Hokkaido Eastern Iburi Earthquake (M w 6.6) on September 6, 2018. The study area is characterized by gently undulating terrain that is finely dissected by shallow streams and covered predominantly by layers of volcanic products with high water content. Most of the landslides were shallow landslides, and their slip surfaces often formed in a layer of volcanic soil called the "Ta-d, " deposited at 9000 ybp. Low ridges separating small catchments allowed individual landslides to coalesce in many locations. The average size of landslides was 7160 m 2. Landslide size tended to increase with slope angle up to 20° to 25° and then decrease with further increase of slope angle. About half of the landslides occurred in a feature with both concave planform and profile curvature, and their average size was 8720 m 2. In contrast, 17% of the total landslides occurred in the case of both curvatures being convex, and their average size was 5190 m 2. The results indicated that the accumulation of saturated soil in concave features provided more opportunities for landslides of large sizes. The frequency-size distribution of the landslides presented high rollover, 5.0 × 10 −3 km 2 , but the exponent of power law decay for medium to large landslides, − 2.46, was not largely different from those of studies in other locations. Compared with other seismically caused examples, the landslides triggered by the Hokkaido Eastern Iburi Earthquake can be characterized as more clustered, more numerous, and larger in size for the moment magnitude of the earthquake. Conversely, the magnitude scale for the landslide event estimated from the total landslide area was equivalent to that of a region struck by an earthquake of M w = 7.0 to 7.4. This study demonstrated that gently undulating regions can produce unexpectedly large and frequent landslides when struck by an intense earthquake, and when soil layers vulnerable to ground shaking cover the ground.

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“…Size statistics of landslides are analyzed using frequencyarea distribution curves of landslides (e.g., Malamud et al, 2004). There is a large amount of literature arguing that the frequency-area distribution of medium and large landslides has a power-law distribution which diverges from the power law towards smaller sizes (e.g., Hovius et al, 1997Hovius et al, , 2000Malamud et al, 2004). Given this argument, we can identify the divergence point of the frequency-area distribution curve to determine site-specific threshold values referring to the limit between medium and small landslides.…”

Section: Landslide Frequency-area Distributionsmentioning

confidence: 99%

“…Some studies took independent earthquake-and rainfalltriggered landslide inventories to compare the characteristics of landslides induced by different triggers. Malamud et al (2004) compared earthquake-triggered landslides from the Northridge earthquake, Umbria snowmelt-triggered landslide, and Guatemala rainfall-triggered landslide as examples and concluded that the three frequency-area distributions were in good agreement with each other. compared earthquake-triggered landslides, from Northridge, Chi-Chi and Finisterre Mountains (Papua New Guinea), to evaluate topographic site effects on the distribution of landslides.…”

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confidence: 95%

How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, central Himalaya

Zhang

Westen

Tanyaş

et al. 2019

Nat. Hazards Earth Syst. Sci.

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Inventories of landslides caused by different triggering mechanisms, such as earthquakes, extreme rainfall events or anthropogenic activities, may show different characteristics in terms of distribution, contributing factors and frequency-area relationships. The aim of this research is to study such differences in landslide inventories and the effect they have on landslide susceptibility assessment. The study area is the watershed of the transboundary Koshi River in the central Himalaya, shared by China, Nepal and India. Detailed landslide inventories were generated based on visual interpretation of remote-sensing images and field investigation for different time periods and triggering mechanisms. Maps and images from the period 1992 to 2015 were used to map 5858 rainfall-triggered landslides, and after the 2015 Gorkha earthquake, an additional 14 127 coseismic landslides were mapped. A set of topographic, geological and land cover factors were employed to analyze their correlation with different types and sizes of landslides. The frequency-area distributions of rainfall-and earthquake-triggered landslides (ETLs) have a similar cutoff value and power-law exponent, although the ETLs might have a larger frequency of a smaller one. In addition, topographic factors varied considerably for the two triggering events, with both altitude and slope angle showing significantly different patterns for rainfall-triggered and earthquake-triggered landslides. Landslides were classified into two size groups, in combination with the main trigger-ing mechanism (rainfall-or earthquake-triggered). Susceptibility maps for different combinations of landslide size and triggering mechanism were generated using logistic regression analysis. The different triggers and sizes of landslide data were used to validate the models. The results showed that susceptible areas for small-and large-size rainfall-and earthquake-triggered landslides differed substantially.

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The role of topography in the scaling distribution of landslide areas: A cellular automata modeling approach

Cited by 28 publications

References 51 publications

Landslide Susceptibility Modeling Using Integrated Ensemble Weights of Evidence with Logistic Regression and Random Forest Models

Landslide Susceptibility Modeling Using Integrated Ensemble Weights of Evidence with Logistic Regression and Random Forest Models

Topographic effects on frequency-size distribution of landslides triggered by the Hokkaido Eastern Iburi Earthquake in 2018

How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, central Himalaya

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