Simulation of Different SPI Models

Sharma, Bharti; Sharma, Neeraj; Sharma, Neeshu

doi:10.5120/227-378

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…Topographic wetness index (TWI), which was reclassified in standard deviation from 4.7 m to 17.9 m (Rodhe and Seibert, 1999;Zinko et al, 2005), expresses a potential index of saturation of soils (Sharma, 2010). Topographic roughness (ROUGH) is a measure of the texture of a surface and was reclassified in 5 classes, from 1 to 1.9 by natural breaks (Hobson, 1972).…”

Section: Factor Selectionmentioning

confidence: 99%

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Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain)

Costanzo

Rotigliano

Irigaray

et al. 2012

Nat. Hazards Earth Syst. Sci.

179

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Abstract.A procedure to select the controlling factors connected to the slope instability has been defined. It allowed us to assess the landslide susceptibility in the Rio Beiro basin (about 10 km 2 ) over the northeastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed us to generate a landslide inventory consisting in 127 phenomena. To discriminate between stable and unstable conditions, a diagnostic area had been chosen as the one limited to the crown and the toe of the scarp of the landslide. 15 controlling or determining factors have been defined considering topographic, geologic, geomorphologic and pedologic available data. Univariate tests, using both association coefficients and validation results of singlevariable susceptibility models, allowed us to select the best predictors, which were combined for the unique conditions analysis. For each of the five recognised landslide typologies, susceptibility maps for the best models were prepared. In order to verify both the goodness of fit and the prediction skill of the susceptibility models, two different validation procedures were applied and compared. Both procedures are based on a random partition of the landslide archive for producing a test and a training subset. The first method is based on the analysis of the shape of the success and prediction rate curves, which are quantitatively analysed exploiting two morphometric indexes. The second method is based on the analysis of the degree of fit, by considering the relative error between the intersected target landslides by each of the different susceptibility classes in which the study area was partitioned. Both the validation procedures confirmed a very good predictive performance of the susceptibility models and of the actual procedure followed to select the controlling factors.

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Section: Factor Selectionmentioning

confidence: 99%

“…Stream power index (SPI) is the time rate of energy expenditure and has been used as a measure of the erosive power, which can control the initiation of landslides. SPI can be calculated as: SPI = As tan β, where As specific catchment area and tan β is local slope (Sharma, 2010). Geological l.s.…”

Section: Factor Selectionmentioning

confidence: 99%

Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain)

Costanzo

Rotigliano

Irigaray

et al. 2012

Nat. Hazards Earth Syst. Sci.

179

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Prioritization of Landslide Effective Factors using Logistic Regression (Case Study: A part of KopeDagh-HezarMasjedZone)

Bastami

Memarian

Tajbakhsh

et al. 2019

jwmr

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Landslideeventin Iran, as a natural hazard, causes a lot of mortal and financial losses annually. Thus, the comprehensive researches are necessary to provide useful solution for preventing and reducing the damages caused by landslide events. Accordingly, the present study uses a logistic regression approach whit the aim of prioritizing the factors affecting the occurrence of landslides in a part of KopetDagh-HezarMasjed zone, in NorthEast of Iran. In this work, after applying the GIS functions on each initial information layer,the logistic regression analysis was performed to identify the effective factors, and then the frequency of landslides in each class was determined. Based on the results of Type II analysis, among all selected factors, soil factor with the lowest value of Pr>LR ratio (.) was identified as the most important driving force in landslide happening.

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Health traditions of Sikkim Himalaya

Panda¹,

Misra²

2010

J Ayurveda Integr Med

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Ancient medical systems are still prevalent in Sikkim, popularly nurtured by Buddhist groups using the traditional Tibetan pharmacopoeia overlapping with Ayurvedic medicine. Traditional medical practices and their associated cultural values are based round Sikkim’s three major communities, Lepcha, Bhutia and Nepalis. In this study, a semi-structured questionnaire was prepared for folk healers covering age and sex, educational qualification, source of knowledge, types of practices, experience and generation of practice, and transformation of knowledge. These were administered to forty-eight folk healers identified in different parts of Sikkim.490 medicinal plants find their habitats in Sikkim because of its large variations in altitude and climate. For 31 commonly used by these folk healers, we present botanical name, family, local name, distribution, and parts used, together with their therapeutic uses, mostly Rheumatoid arthritis, Gout, Gonorrhea, Fever, Viral flu, asthma, Cough and Cold, indigestion, Jaundice etc. A case treated by a folk healer is also recounted. This study indicates that, in the studied area, Sikkim’s health traditions and folk practices are declining due to shifts in socio-economic patterns, and unwillingness of the younger generation to adopt folk healing as a profession.

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Simulation of Different SPI Models

Cited by 3 publications

References 5 publications

Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain)

Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain)

Prioritization of Landslide Effective Factors using Logistic Regression (Case Study: A part of KopeDagh-HezarMasjedZone)

Health traditions of Sikkim Himalaya

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