Article

Probabilistic landslide hazard assessment using homogeneous susceptible units (HSU) along a national highway corridor in the northern Himalayas, India

Landslides (Impact Factor: 2.87). 09/2011; 8(3):293-308. DOI: 10.1007/s10346-011-0257-9

ABSTRACT

The increased socio-economic significance of landslides has resulted in the application of statistical methods to assess their
hazard, particularly at medium scales. These models evaluate where, when and what size landslides are expected. The method presented in this study evaluates the landslide hazard on the basis of homogenous susceptible
units (HSU). HSU are derived from a landslide susceptibility map that is a combination of landslide occurrences and geo-environmental
factors, using an automated segmentation procedure. To divide the landslide susceptibility map into HSU, we apply a region-growing
segmentation algorithm that results in segments with statistically independent spatial probability values. Independence is
tested using Moran’s I and a weighted variance method. For each HSU, we obtain the landslide frequency from the multi-temporal data. Temporal and
size probabilities are calculated using a Poisson model and an inverse-gamma model, respectively. The methodology is tested
in a landslide-prone national highway corridor in the northern Himalayas, India. Our study demonstrates that HSU can replace
the commonly used terrain mapping units for combining three probabilities for landslide hazard assessment. A quantitative
estimate of landslide hazard is obtained as a joint probability of landslide size, of landslide temporal occurrence for each
HSU for different time periods and for different sizes.

KeywordsLandslides–Hazard–HSU–Segmentation–Himalayas–India

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    • "In mountainous terrain, the occurrence of landslides are influenced by various causative factors and triggered by several external factors, such as intense rainfall, earthquake shaking, water level change, storm waves and rapid stream erosion etc., (Naranjo et al. 1994; Dai et al. 2002). In addition, the human intervention on hill slope for construction of roads, urban expansion, deforestation, and rapid changes on land use practice contribute to slope instability (Das et al. 2011). Landslide susceptibility refers to the probability of occurrence of landslide in an area based on the correlation between causative factors and spatial distribution of landslides (Brabb 1984). "

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    • "In addition, extensive human interference in hill slope areas for the construction of roads, urban expansion along the hill slopes, deforestation and rapid change in land use contribute to instability. This makes it difficult, if not impossible, to define a single methodology to identify and map landslides, to ascertain landslide hazards and to evaluate the associated risk (Guzzetti et al. 2005; Das et al. 2011). In this study, topography, geology, climate, vegetation and anthropogenic factors were selected based on expert knowledge, on the basis of field studies related to active landslides. "
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    ABSTRACT: The GIS-multicriteria decision analysis (GIS-MCDA) technique is increasingly used for landslide hazard mapping and zonation. It enables the integration of different data layers with different levels of uncertainty. In this study, three different GIS-MCDA methods were applied to landslide susceptibility mapping for the Urmia lake basin in northwest Iran. Nine landslide causal factors were used, whereby parameters were extracted from an associated spatial database. These factors were evaluated, and then, the respective factor weight and class weight were assigned to each of the associated factors. The landslide susceptibility maps were produced based on weighted overly techniques including analytic hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA). An existing inventory of known landslides within the case study area was compared with the resulting susceptibility maps. Respectively, Dempster-Shafer Theory was used to carry out uncertainty analysis of GIS-MCDA results. Result of research indicated the AHP performed best in the landslide susceptibility map-ping closely followed by the OWA method while the WLC method delivered significantly poorer results. The resulting figures are generally very high for this area, but it could be proved that the choice of method significantly influences the results.
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    • "Sendo a suscetibilidade a componente espacial da perigosidade, pode obter-se a localização do risco (não quantificado) através do seu cruzamento com os elementos expostos. Nestes elementos, destaca-se as estradas pela frequência com que são afetadas por movimentos de vertente, devendo-se a maioria dos casos ao corte e abertura de taludes (por vezes mal dimensionados) para a sua construção, fatores que põem em causa a sustentação do material que compõe a vertente (Highland e Bobrowsky, 2008; Das et al., 2011). Os movimentos de vertente, dependendo da sua magnitude, podem destruir ou interromper estas infraestruturas e, deste modo, originar diversos condicionalismos, ao interferir no tempo de reação dos meios operacionais (Meneses e Zêzere, 2012). "

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