The volume-to-surface-area ratio constrains the rollover of the power law distribution for landslide size

Li, Langping; Lan, Hengxing; Wu, Yuming

doi:10.1140/epjp/i2014-14089-y

Cited by 12 publications

(10 citation statements)

References 36 publications

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“…To do so, we first identified the cutoff point for fitting and β based on the method of Clauset et al . (), which has been applied elsewhere to landslide frequency‐area statistics (Bennett et al ., ; Hurst et al ., ; Urgeles and Camerlenghi, ; Li et al ., ; Parker et al ., ). This approach estimates possible β values for each possible cutoff value using maximum‐likelihood fitting methods with goodness‐of‐fit tests based on the Kolmogorov–Smirnov (KS) statistic and likelihood ratios.…”

Section: Methodsmentioning

confidence: 98%

“…Step 2: Obtain the cutoff point and power-law exponent For each inventory, we found the power-law exponent (β) and the best-fitting constant (c 0 ) of the power-law and assessed the corresponding mLS value. To do so, we first identified the cutoff point for fitting and β based on the method of Clauset et al (2009), which has been applied elsewhere to landslide frequency-area statistics (Bennett et al, 2012;Hurst et al, 2013;Urgeles and Camerlenghi, 2013;Li et al, 2014b;Parker et al, 2015). This approach estimates possible β values for each possible cutoff value using maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic and likelihood ratios.…”

Section: Methodsmentioning

confidence: 99%

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An updated method for estimating landslide‐event magnitude

Tanyaş

Allstadt

Westen

2018

Earth Surf Processes Landf

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Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

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Section: Methodsmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 99%

An updated method for estimating landslide‐event magnitude

Tanyaş

Allstadt

Westen

2018

Earth Surf Processes Landf

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“…(6) makes it possible to inspect how the parameter estimation of landslide area distribution affects the estimation of landslide erosion rate. In our study, the relationship V = 2.59A 1.05 deduced from the Fujian historical landslide inventory (Li et al 2014) is used, and Eq. (y6) is calculated numerically.…”

Section: Average Landslide Volumementioning

confidence: 99%

How sample size can effect landslide size distribution

Lan

2016

Geoenviron Disasters

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Background: Landslide size distribution is widely found to obey a negative power law with a rollover in the smaller size, and has been exploited by many researchers to inspect landside physics or to assess landslide erosion and landslide hazard. Yet, sample size has effect on the statistics of landslide size even though we manage to avoid complications associated with landslide datasets and statistical treatments. Results: In this paper, a series of stochastic simulations were implemented to explicitly and systematically quantify the effect of sample size. The results show that, the errors of parameters estimated based on small sample size can be considerably large. For a sample size of 100, the relative error of the estimated landslide erosion rate that has a probability of 50 % can approach 100 %. In addition, small sample size also obscures the statistical significance of the variances in parameters between different subsets of the same dataset. Although inconsistency was found regarding how the power exponent varies with rainfall intensity, numerical results suggest that the variance observed in a dataset with a small sample size may be not statistically significant.

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“…To do so, we first identified the cutoff point for fitting and β based on the method of Clauset et al (2009), which has been applied elsewhere to landslide frequency-area statistics (e.g. Bennett et al, 2012;Hurst et al, 2013;Li et al, 2014b;Parker et al, 2015;Urgeles and Camerlenghi, 2013). This approach estimates possible β values for each possible cutoff values using maximumlikelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic and likelihood ratios.…”

Section: Step 2: Obtain the Cutoff Point And Power-law Exponentmentioning

confidence: 99%

“…These failures have a wide range of depths and make up the power-law tail. Li et al (2014b) expanded on this idea in a three-dimensional perspective and proposed that the power-law divergence is linked to the volume-to-surface-area ratio of landslides. Decreasing this ratio causes an increase in resistance force without significantly changing the driving force.…”

Section: Introductionmentioning

confidence: 99%

Rapid assessment of earthquake-induced landslides

Tanyaş¹

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The volume-to-surface-area ratio constrains the rollover of the power law distribution for landslide size

Cited by 12 publications

References 36 publications

An updated method for estimating landslide‐event magnitude

An updated method for estimating landslide‐event magnitude

How sample size can effect landslide size distribution

Rapid assessment of earthquake-induced landslides

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