Landslide hazard zoning using the GIS approach—A case study from the Ramganga catchment, Himalayas

Gupta, Rakesh; Joshi, B.C.

doi:10.1016/0013-7952(90)90037-2

Cited by 225 publications

(88 citation statements)

References 5 publications

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“…Mapping or delineating areas prone to landsliding is essential for land-use activities and management decision making in hilly or mountainous regions. A landslide hazard map can be constructed by a qualitative combination of maps of site conditions, including geology, topography and geomorphology (Gupta and Joshi, 1989;Anbalagan, 1992), by statistical methods, e.g. discriminant analysis and regression techniques, which correlate landslide occurrence with geologic and geomorphic factors (Rice and Pillsbury, 1982;Lewis and Rice, 1990;Carrara et al, 1991;Mark and Ellen, 1995;Atkinson and Massari, 1998), or by using safety factors from stability analysis (Okimura and Kawatani, 1987).…”

Section: Introductionmentioning

confidence: 99%

A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression

Dai

Lee

2003

Earth Surf Processes Landf

158

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Landslides constitute one of the major natural hazards that could cause significant losses of life and property. Mapping or delineating areas prone to landsliding is therefore essential for land-use activities and management decision making in hilly or mountainous regions. A landslide hazard map can be constructed by a qualitative combination of maps of site conditions, including geology, topography and geomorphology, by statistical methods through correlating landslide occurrence with geologic and geomorphic factors, or by using safety factors from stability analysis. A landslide hazard map should provide information on both the spatial and temporal probabilities of landsliding in a certain area. However, most previous studies have focused on susceptibility mapping, rather than on hazard mapping in a spatiotemporal context. This study aims at developing a predictive model, based on both quasi-static and dynamic variables, to determine the probability of landsliding in terms of space and time. The study area selected is about 13 km 2 in North Lantau, Hong Kong. The source areas of the landslides caused by the rainstorms of 18 July 1992 and 4-5 November 1993 were interpreted from multi-temporal aerial photographs. Landslide data, lithology, digital elevation model data, land cover, and rainfall data were digitized into a geographic information system database. A logistic regression model was developed using lithology, slope gradient, slope aspect, elevation, slope shape, land cover, and rolling 24 h rainfall as independent variables, since the dependent variable could be expressed in a dichotomous way. This model achieved an overall accuracy of 87Ð2%, with 89Ð5% of landslide grid cells correctly classified and found to be performing satisfactorily. The model was then applied to rainfalls of a variety of periods of return, to predict the probability of landsliding on natural slopes in space and time. It is observed that the modelling techniques described here are useful for predicting the spatiotemporal probability of landsliding and can be used by land-use planners to develop effective management strategies.

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Section: Introductionmentioning

confidence: 99%

A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression

Dai

Lee

2003

Earth Surf Processes Landf

158

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“…It is easier to manage and enables the introduction of expert opinion into the analysis with respect with other methods more computationally demanding in processing large data-sets, especially considering the scale of the study. The proposed method is derived from a heuristic 'ranking and rating' index-based approach (Stevenson 1977;Amadesi & Vianello 1978;Romana 1985;Gupta & Joshi 1990;Anbalagan 1992;Gupta & Anbalagan 1997;Budetta et al 2008), modified through a bivariate statistical procedure (Van Westen 1993) for assigning the weights to the factors influencing slope instability. The susceptibility was obtained as polynomial function of predisposing factors, according to the following expression:…”

Section: Susceptibility Modelling and Performance Analysismentioning

confidence: 99%

GIS-based predictive models for regional-scale landslide susceptibility assessment and risk mapping along road corridors

Pellicani

Argentiero

Spilotro

2017

Geomatics, Natural Hazards and Risk

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In this paper, a study aimed to assess the landslide susceptibility at a regional scale for the wide provincial territory of Matera (Basilicata region, southern Italy) and the relative risk along the main road corridors distributed in this area is presented. A heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area by using a polynomial function of eight predisposing factors, weighted according to their influence on the instability process. The resulting susceptibility map was successively used for assessing the landslide risk along the provincial road network. The importance of these roads, representing the main network connecting the urban centres, derives from the absence of an efficient integrated transportation system through the entire regional territory. The landslide risk was evaluated through a matricial approach, which has allowed to define the risk levels (low, medium and high) along road stretches by overlapping the consequences and hazard maps, by combining their corresponding classes in a matrix and by associating to each combination a risk level. The resulting landslide risk map provides support information for decision-making and for identifying the priorities for the design of appropriate mitigation plans.

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“…4 shows that 8 contours (No. 7,16,17,21,23,25,28,29) represent the areas of low or very low risk of hazard of sliding. Although the risk of landside is lessened due to the spread of low-incline slopes, the seismicity reaches up to 8 points, while rocks are of high hazard of sliding.…”

Section: Figure 5 Landscape and Environmental Risks And Hazards Causmentioning

confidence: 99%

The Assessment of Landscape and Environmental Risks and Hazards Caused by Landslides in Mountain Areas

Alizade¹

2016

Appl Ecol Env Res

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Abstract. The landslide is a kind of natural disaster responsible for creation of risks and hazards in relation to population and its economic activity. Each year the occurrence of landslides causes killing of people and economic losses, as well as leads to destruction and deterioration of pastures, arable lands, forests and highways. The southeastern slope of Greater Caucasus is one of the most active landslide zones in Azerbaijan. As a result of the occurrence of landslide in the Mughanli area in 2011, 168 houses out of 279 ones became unusable while the village of the same name was moved to a new residential area. Moreover, the 3 km-long part of the Ismayilli-Mughanli-Shamakhi highway near the village became unusable repeatedly. In 2014, USD 52 million was spent in order to eliminate the consequences of landslides. Topographic maps of scale of 1:10000 and also aerospace images were used to assess the landscape-and environmental risks and hazards caused by landslides. Maps of various factors of the same scales, compiled in ArcGIS program were analysed through GIS technologies, which allowed compilation of a map of relevant landscape-and environmental risks and hazards. The carried out studies will enable to estimate natural disasters and reduce the related economic losses.

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Landslide hazard zoning using the GIS approach—A case study from the Ramganga catchment, Himalayas

Cited by 225 publications

References 5 publications

A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression

A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression

GIS-based predictive models for regional-scale landslide susceptibility assessment and risk mapping along road corridors

The Assessment of Landscape and Environmental Risks and Hazards Caused by Landslides in Mountain Areas

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