Topographic Correction of Wind-Driven Rainfall for Landslide Analysis in Central Taiwan with Validation from Aerial and Satellite Optical Images

Liu, Jin-King; Shih, Po-Tsung

doi:10.3390/rs5062571

Cited by 32 publications

(23 citation statements)

References 24 publications

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“…On the other hand, they are not completely satisfactory in estimating the correct precipitation amount [249]. The prediction of rainfall intensity can benefit from correction of the effects due to local topography, as demonstrated in [271].…”

Section: Triggering Factorsmentioning

confidence: 99%

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally divided into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy. The first class comprehends techniques for landslide recognition, i.e., the mapping of past or active slope failures. The second regards landslide monitoring, which entails both ground deformation measurement and the analysis of any other changes along time (e.g., land use, vegetation cover). The third class groups methods for landslide hazard analysis and forecasting. The aim of this paper is to give an overview on the applications of remote-sensing techniques for the three categories of landslide investigations, focusing on the achievements of the last decade, being that previous studies have already been exhaustively reviewed in the existing literature. At the end of the paper, a new classification of remote-sensing techniques that may be pertinently adopted for investigating specific typologies of soil and rock slope failures is proposed.

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Section: Triggering Factorsmentioning

confidence: 99%

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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“…This suggests that concave slopes are more vulnerable to shallow landslides due to running water concentration and the build-up of pore pressure [49]. Wind is also taken to be a crucial element which affects rainfall intensity on various slope aspects [50]. The landslide is highly susceptible on SE slope aspects.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

Lee

Hong

2017

Journal of Sensors

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This paper assesses the performance of the landslide susceptibility analysis using frequency ratio (FR) with an iterative random sampling. A pair of before-and-after digital aerial photographs with 50 cm spatial resolution was used to detect landslide occurrences in Yongin area, Korea. Iterative random sampling was run ten times in total and each time it was applied to the training and validation datasets. Thirteen landslide causative factors were derived from the topographic, soil, forest, and geological maps. The FR scores were calculated from the causative factors and training occurrences repeatedly ten times. The ten landslide susceptibility maps were obtained from the integration of causative factors that assigned FR scores. The landslide susceptibility maps were validated by using each validation dataset. The FR method achieved susceptibility accuracies from 89.48% to 93.21%. And the landslide susceptibility accuracy of the FR method is higher than 89%. Moreover, the ten times iterative FR modeling may contribute to a better understanding of a regularized relationship between the causative factors and landslide susceptibility. This makes it possible to incorporate knowledge-driven considerations of the causative factors into the landslide susceptibility analysis and also be extensively used to other areas.

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“…Liu and Shih [57] took into account the effects of wind-driven rainfall as a significant factor in landslides that occurred in Taiwan during Typhoon Mindulle. Similarly, Rogers et al [58] developed another approach to consider oblique rainfall-aspect in Himalayan Mountains of Northern Pakistan based on directional monsoon effects.…”

Section: Acquisition Of Rainfall Datamentioning

confidence: 99%

Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

Guimarães

Machado

Júnior

et al. 2017

IJGI

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Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission) data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a) creating the digital elevation model (DEM) and deriving attributes such as slope and contributing area; (b) incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c) quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.

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Topographic Correction of Wind-Driven Rainfall for Landslide Analysis in Central Taiwan with Validation from Aerial and Satellite Optical Images

Cited by 32 publications

References 24 publications

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

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