Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale

Jebur, Mustafa Neamah; Pradhan, Biswajeet; Tehrany, Mahyat Shafapour

doi:10.1016/j.rse.2014.05.013

Cited by 289 publications

(161 citation statements)

References 61 publications

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“…LSM requires that topographic, environmental, geological and hydrological parameters should be taken into account. Some researchers assume that the accuracy of the created susceptibility map increases proportionally with the quantity of LCFs used (Jebur et al 2014). Other scientists state that a small number of LCFs is satisfactory to produce landslide susceptibility maps with a reasonable quality (Jebur et al 2014;Mahalingam et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers assume that the accuracy of the created susceptibility map increases proportionally with the quantity of LCFs used (Jebur et al 2014). Other scientists state that a small number of LCFs is satisfactory to produce landslide susceptibility maps with a reasonable quality (Jebur et al 2014;Mahalingam et al 2016). The investigations of Kingsbury et al (1992) present that the additional factors (soil type, land use, slope aspect, proximity to watercourses) did not increase the reliability of the susceptibility maps and are suitable to a particular study area only.…”

Section: Introductionmentioning

confidence: 99%

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Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Pawłuszek

Borkowski

2016

Nat Hazards

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Choosing appropriate landslide-controlling factors (LCFs) in landslide susceptibility mapping (LSM) is a challenging task and depends on the nature of terrain and expert knowledge and experience. Nowadays, it is very common to use digital elevation model (DEM) and DEM-derivatives, as a representation of the topographic conditions. The objective of this study is to explore topography in depth and simultaneously reduce redundant information within DEM-derivatives using principal component analysis. Moreover, this study investigates the impact of DEM-derived factors on LSM. Therefore, three various strategies were tested. The first strategy included a set of LCFs created from the four initial principal components, which were provided from DEM-derived factors. The second strategy included a set of parameters which contained additional lithological and environmental factors. The third strategy utilises the analytical hierarchy process (AHP) to assign weights to each LCF. The LSM was performed based on landslide susceptibility index. Obtained results show that 60% of existing landslides fell into high and very high susceptibility zones using first and second strategies. It proves that topographic factors play a significant role in LSM. Adding additional lithological and environmental factors to the set of LCFs did not improve the results significantly, unless the AHP was used in the third strategy. It improved results significantly; up to 70%. Results from second and third strategies highlight utility of AHP in LSM. Presented studies were performed on the area very prone to landslide occurrence in the region of Ro_ znów Lake, Poland.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Pawłuszek

Borkowski

2016

Nat Hazards

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“…Stream power index (SPI) is a function of the product of flow accumulation and the local slope that describes the potential erosion power at a specific point of the surface [24,25].…”

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confidence: 99%

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

et al. 2017

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Large areas in southern Kyrgyzstan are subjected to high and ongoing landslide activity; however, an objective and systematic assessment of landslide susceptibility at a regional level has not yet been conducted. In this paper, we investigate the contribution that remote sensing can provide to facilitate a quantitative landslide hazard assessment at a regional scale under the condition of data scarcity. We performed a landslide susceptibility and hazard assessment based on a multi-temporal landslide inventory that was derived from a 30-year time series of satellite remote sensing data using an automated identification approach. To evaluate the effect of the resulting inventory on the landslide susceptibility assessment, we calculated an alternative susceptibility model using a historical inventory that was derived by an expert through combining visual interpretation of remote sensing data with already existing knowledge on landslide activity in this region. For both susceptibility models, the same predisposing factors were used: geology, stream power index, absolute height, aspect and slope. A comparison of the two models revealed that using the multi-temporal landslide inventory covering the 30-year period results in model coefficients and susceptibility values that more strongly reflect the properties of the most recent landslide activity. Overall, both susceptibility maps present the highest susceptibility values for similar regions and are characterized by acceptable to high predictive performances. We conclude that the results of the automated landslide detection provide a suitable landslide inventory for a reliable large-area landslide susceptibility assessment. We also used the temporal information of the automatically detected multi-temporal landslide inventory to assess the temporal component of landslide hazard in the form of exceedance probability. The results show the great potential of satellite remote sensing for deriving detailed and systematic spatio-temporal information on landslide occurrences, which can significantly improve landslide susceptibility and hazard assessment at a regional scale, particularly in data-scarce regions such as Kyrgyzstan.

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“…Based on the given texture, the soil type is clay loam. This is substantiated by Jebur et al [19]. Malaysia is a tropical country.…”

Section: Location and Geology Of The Landslide Areamentioning

confidence: 64%

Analytical study of the causes of the major landslide of Bukit Antarabangsa in 2008 using fault tree analysis

Kazmi

Qasim

Harahap

et al. 2017

Innov. Infrastruct. Solut.

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Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale

Cited by 289 publications

References 61 publications

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

Analytical study of the causes of the major landslide of Bukit Antarabangsa in 2008 using fault tree analysis

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