Landslide hazard zonation mapping and cut slope stability analyses along Yercaud ghat road (Kuppanur–Yercaud) section, Tamil Nadu, India

Ramesh, V.; Mani, S.; Baskar, M.; Kavitha, G.; Anbazhagan, S.

doi:10.1186/s40703-017-0039-x

Cited by 12 publications

(6 citation statements)

References 53 publications

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“…The ghat section was buffered 2) for individual parameter [6,12] . The highest weight assigned to landslide inventory (20), slope (16), relief (12), lithology (12) and rainfall (08) based on their importance and triggering intensity in the landslide frequency. Final landslide hazard zonation (LHZ) map of the study area prepared by using the weight base multi-criteria overlay method in GIS domain using ArcGIS 10.5 software.…”

Section: Methodsmentioning

confidence: 99%

“…They calculated LHEF rating scheme and the total estimated hazard (TEHD) as per the Bureau of Indian Standard (BIS) guidelines (IS: 14496 (Part-2) 1998). Ramesh et al [16] examined the landslide hazard zonation mapping and cut slope stability analyses along Yercaud ghat road (Kuppanur -Yercaud) section, Tamil Nadu, India, in this research they prepare macro LHZ map using the landslide hazard evaluation factor (LHEF) rating scheme proposed by Bureau of Indian Standard IS 14496 (Part-2) 1998. Chingkhei R. K. et al [2] prepare landslide hazard zonation in NH-1A in Kashmir, Himalaya, India, using GIS and remote sensing data.…”

Section: [1]mentioning

confidence: 99%

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Landslide Hazard Zonation along the MH SH-73 at Kelghar Ghat, Satara, Maharashtra

Karande

2021

Int J Res Rev

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Road transportation is the most common victim of landslide in the world. The present study investigates the landslide hazard zonation along the MH SH-73 at Kelghar ghat between Medha and Mahabaleshwar hill station of Maharashtra. Remote Sensing and GIS were used for the landslide hazard zonation of this section. The ghat section was buffered 100 m on both side to define the extent of study area based on the field investigation. The study incorporated predefined important landslide causative factors, viz. slope, rainfall, relief, lithology, soil depth, soil erosion, soil texture, land use / land cover, drainage distance, drainage density, lineament distance, lineament density, aspect, temperature, landslide inventory and in this approach fifteen thematic layers were prepared in GIS platform. The weight and score were assigned to each thematic layer based on heuristic approach on their relative importance in causing landslide. Multi-criteria model in ArcGIS 10.5 software were used for the mapping landslide hazard zones and it were classified into six zones: very high (1.3 %), high (1.7 %), moderate (3.4 %), low (7.6 %) very low (8.4 %) and no risk zone (77.7 %). The final result of this research can help for proper mitigation and adaptation measures for engineers, planners and administrators for this ghat section. Keywords: GIS, Landslide Hazard Zonation, Remote Sensing, Susceptibility, Sahyadri, Kelghar.

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Section: Methodsmentioning

confidence: 99%

Section: [1]mentioning

confidence: 99%

Landslide Hazard Zonation along the MH SH-73 at Kelghar Ghat, Satara, Maharashtra

Karande

2021

Int J Res Rev

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“…The major pitfalls are inadequate understanding of the underlying mechanism of slope failure and the interplay of causative factors of slope failures. However, recently, ample pioneering work has been done by many researchers employing conventional and numerical simulation approaches, and a much better understanding of rock slope engineering practices has been achieved [13,14,18,20,22,23,38,50,51,55,61]. In different sections of the Uttarakhand Himalayas, noteworthy studies on slope stability have been carried out by various researchers and organizations, which have provided reasonable and rational insights into environmental fragility, particularly in areas traversed by major and minor tectonic structures [18,20,52,54,60,67,69].…”

Section: Introductionmentioning

confidence: 99%

Stability appraisal of road cut slopes along a strategic transportation route in the Himalayas, Uttarakhand, India

Siddique

Khan

2019

SN Appl. Sci.

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In precarious mountain terrains like the Himalayas, road cut slopes are highly vulnerable to slope failures. Slope failures in the region are often triggered by natural factors such as neotectonism, rainfall, seismicity, weathering, erosion, etc. However, rapid human intervention is an additional factor causing large-scale slope instability in the region. Unplanned excavations of slopes for construction and/or widening of roads decrease slope stability. The inevitable slope failures cause major inconvenience to tourists and residents and are also responsible for severe injuries and loss of lives and property. The present study incorporates a stability analysis of road cut slopes along National Highway 58 (NH-58) from Kaliyasaur to Rudraprayag, Uttarakhand. Vulnerable slopes were identified during the field survey. To evaluate stability conditions of rock mass, rock mass classification systems including rock mass rating (RMR), continuous slope mass rating and the Geological Strength Index (GSI) were employed to identify different stability grades. Furthermore, quantified GSI was correlated with basic RMR in a bivariate plot, which showed a linear relationship. Kinematic analysis was also carried out to identify the probability of structurally controlled failures due to adversely oriented discontinuities. Outcomes from different methods corroborated each other and matched the existing site conditions.

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“…This leads to biasness in the results and the output tends to give the results based on the initial weight given by the author. When such models, where user gives ranking based on earlier experiences, are used for preparation of LSZ map (Rawat et al 2015;Ghosh et al 2017;Ramesh et al 2017), the choice of rating needs to be analysed. Depending on the number of layers being used in the analysis, the combination of these ratings will vary in factorial terms.…”

Section: Introductionmentioning

confidence: 99%

Selection of weightages for causative factors used in preparation of landslide susceptibility zonation (LSZ)

Gupta

Shukla

Thakur

2018

Geomatics, Natural Hazards and Risk

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Most of the models for landslide susceptibility zonation (LSZ) except machine learning needs manual selection of weights or ratings, which are given by expertise knowledge, leading to subjectivity and specificity. Hence, selection of ratings is very important in the preparation of LSZ maps. Here, seven layers/factors viz. aspect, elevation, geology, slope, soil, distance from stream, distance from thrusts are considered for LSZ mapping in Mandakini River basin, Uttarakhand containing 1,805,636 pixels. The weights were calculated using information value (InfoVal) method. The occurrences of landslides (2009 pixels) until 2008 were considered for training of model. Thus for giving rating to each thematic layer, 7! = 5040 permutations (ratings) are possible. Hence, 5040 LSZ maps were prepared and out of them, the best rating was identified using fisher discriminant analysis (FDA) and binary logistic regression (LR). FDA and LR gave similar ratings and the correlation (r 2 ) between their weights was 0.9226. Thematic layers were then multiplied by the corresponding ratings and added to prepare the final LSZ map. The results were validated on the landslide data until 2011, which were not used for training. Out of 223 occurrences of landslides, 39% (87) falls in high susceptible zone followed by 35% (79) in very high susceptible zone according to FDA and similar for LR. The accuracy of the prediction was assessed by Heidke-Skill-Score, which gave score of 0.89 to FDA and 0.90 to LR for 0.5 as threshold of landslide susceptibility index.

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Landslide hazard zonation mapping and cut slope stability analyses along Yercaud ghat road (Kuppanur–Yercaud) section, Tamil Nadu, India

Abstract: Background Landslide is an important natural calamity, which frequently occurs on natural slopes as well as cut slopes of ghat roads in mountainous region, causing risk to human life and properties each year [2, 45]. The occurrence of landslides in mountainous regions is

Cited by 12 publications

References 53 publications

Landslide Hazard Zonation along the MH SH-73 at Kelghar Ghat, Satara, Maharashtra

Landslide Hazard Zonation along the MH SH-73 at Kelghar Ghat, Satara, Maharashtra

Stability appraisal of road cut slopes along a strategic transportation route in the Himalayas, Uttarakhand, India

Selection of weightages for causative factors used in preparation of landslide susceptibility zonation (LSZ)

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