Highways Vs. Landslides and Their Consequences in Himalaya

Kumar, Kishor; Jangpangi, Lalita; Gangopadhyay, S

doi:10.1007/978-3-319-04999-1_55

Cited by 7 publications

(6 citation statements)

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“…When planning a new road, the alignments of the route should be carefully determined considering the probability of landslides during and after construction. The roads are likely to face unexpected problems of slope stability [12]. The quantification of landslide frequency, magnitude and distribution in mountainous terrain is an important consideration in calculating the cost of new roads construction and the maintenance of existing road networks [18].…”

Section: Discussionmentioning

confidence: 99%

“…Every year, landslides kill people and cause huge property damage in mountainous areas of the world [11]. Kumar et al [12] reported that in the Himalayas over 2000 landslides killed more than 5000 people during 2013. In the USA, landslide events cause an estimated US$1-2 billion in economic losses and about 25-50 fatalities annually [13].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the determination of the landslide zone of disturbance is vital for road engineers who must deal with the costly and sometimes life-threatening problems caused by road-induced landslides. Realistic assessment of the impact of proposed transportation construction must be quantifiable as road costs may be significantly increased by landsliding during construction [12,18,24].…”

Section: Introductionmentioning

confidence: 99%

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Physical and Anthropogenic Factors Related to Landslide Activity in the Northern Peloponnese, Greece

Skilodimou

Bathrellos

Koskeridou

et al. 2018

Land

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The geological, geomorphic conditions of a mountainous environment along with precipitation and human activities influence landslide occurrences. In many cases, their relation to landslide events is not well defined. The scope of the present study is to identify the influence of physical and anthropogenic factors in landslide activity. The study area is a mountainous part of the northern Peloponnesus in southern Greece. The existing landslides, lithology, slope angle, rainfall, two types of road network (highway-provincial roads and rural roads) along with land use of the study area are taken into consideration. Each physical and anthropogenic factor is further divided into sub-categories. Statistical analysis of landslide frequency and density, as well as frequency and density ratios, are applied and combined with a geographic information system (GIS) to evaluate the collected data and determine the relationship between physical and anthropogenic factors and landslide activity. The results prove that Plio-Pleistocene fine-grained sediments and flysch, relatively steep slopes (15 • -30 • ) and a rise in the amount of rainfall increase landslide frequency and density. Additionally, Plio-Pleistocene fine-grained sediments and flysch, as well as schist chert formations, moderate (5 • -15 • ) and relatively steep slopes (15 • -30 • ), along with the amount of rainfall of >700 mm are strongly associated with landslide occurrences. The frequency and magnitude of landslides increase in close proximity to roads. Their maximum values are observed within the 50 m buffer zone. This corresponds to a 100 m wide zone along with any type of road corridors, increasing landslide occurrences. In addition, a buffer zone of 75 m or 150 m wide zone along highway and provincial roads, as well as a buffer zone of 100 m or 200 m wide zones along rural roads, are strongly correlated with landslide events. The extensive cultivated land of the study area is strongly related to landslide activity. By contrast, urban areas are poorly related to landslides, because most of them are located in the northern coastal part of the study area where landslides are limited. The results provide information on physical and anthropogenic factors characterizing landslide events in the study area. The applied methodology rapidly estimates areas prone to landslides and it may be utilized for landslide hazard assessment mapping as well as for new and existing land use planning projects.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Physical and Anthropogenic Factors Related to Landslide Activity in the Northern Peloponnese, Greece

Skilodimou

Bathrellos

Koskeridou

et al. 2018

Land

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“…Mountainous areas around the globe have the propensity to be affected by landslides, leading to fatalities and damage to property (Dai et al, 2002). Records show that 200 landslides claimed more than 500 lives in the Himalayas (Kumar et al, 2014). Landslides account for 20-25 fatalities and an estimated US$ 1-2 billion annually in the United States of America (Schuster et al, 1986); and in Italy, a minimum of 263 lives were lost from mass movement in a nine years period (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999) (Guzzetti 3 2000).…”

Section: Introductionmentioning

confidence: 99%

A comparative Geological, Tectonic and Geomorphological assessment of the Charlotte, Regent and Madina Landslides, Western Areas, Sierra Leone

Lahai

Anderson²,

Jalloh

et al. 2020

Preprint

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This work focused on three landslide events that have attracted significant public concern due to the associated calamities. The slides have been analyzed for their geology, tectonics and geomorphological (GTG) characteristics. In addition, an understanding of the link between GTG characteristics and the landslide events was established.To achieve this, field surveys were conducted, particularly for the Charlotte landslide, where identification of geological structures was perturbed by the obliteration of vegetation and sediment accumulations on relatively planar sections of the landslide area. GIS and remote sensing techniques enhanced mapping and determination of landslide characteristics, and laboratory analyses on rock samples provided the petrological characterization of the landslides. Results indicated change in rock composition (gabbro), variable geomorphological characteristics and the nature/pattern and density of discontinuities; these factors, to a large extent, determined the nature and magnitude of the rainfall-triggered landslides. Charlotte lithology slightly differs from and recorded higher Silica (Si) and Aluminum (Al) and lower iron (Fe) than rocks of Regent and Madina landslides. Study also revealed only tenuous correlation between rock composition and weathering depth. The slope angles for the landslides' main scarps (depletion zone) are steep (>45 degree) with altitudes ≈270m, 470m and 200m above sea level for Charlotte, Regent and Madina respectively.Additionally, the area and length of the landslides have relatively high variance (CV=1) and the variance of their run-outs as well is high (CV>1). Finally, information derived from this work can be useful to understand the spatial variation in landslide characteristics and the development of a susceptibility map.

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“…In mountainous regions, these events favor the occurrence of landslides [2,3] and present risks to the population that lives in or travels through these regions. As a result of construction and changes to the soil structure, road edges favor this type of event [4,5]. A previous study [6] analyzed the frequency and distribution of landslides in three hydrographic basins and found that road construction is the most common cause of landslides.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images

Manfré

Nóbrega

Quintanilha

2016

IJGI

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Landslide scar location is fundamental for the risk management process, e.g., it allows mitigation of these areas, decreasing the associated hazards for the population. Remote sensing data usage is an essential tool for landslide identification, mapping, and monitoring. Despite its potential use for landslide risk management, remote sensing usage does have a few drawbacks. The aforementioned events commonly occur at high steep slope regions, frequently associated with shadow occurrence in satellite images, which impairs the identification process and results in low accuracy classifications. In this sense, this paper aims to evaluate the accuracy of different ensembles of multiple classifier systems (MCSs) for landslide scar identification. A severe landslide event on a steep slope with a high rainfall rate area in the southeast region of Brazil was chosen. Ten supervised classifiers were used to identify this severe event and other possible features for the LANDSAT thematic mapper (TM) from June of 2000. The results were evaluated, and nine MCSs were constructed based on the accuracy of the classifiers. Voting was applied through the ensemble method, coupled with contextual analysis and random selection tie-breaker methods. Accuracy was evaluated for each classification ensemble, and a progressive enhancement in the ensemble accuracy was noted as the least accurate classifiers were removed. The best accuracy for landslide identification emerged from the ensemble of the three most accurate classification results. In summary, MCS application generally improved the classification quality and led to fewer omission errors, coupled with a better classification percentage for the 'landslide' class. However, the MCS ensemble algorithm selection must be customized to the purpose of the classification. It is crucial to assess single accuracy indicators of each algorithm to ascertain those with the most consistent performance regarding the final results.

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Highways Vs. Landslides and Their Consequences in Himalaya

Cited by 7 publications

References 1 publication

Physical and Anthropogenic Factors Related to Landslide Activity in the Northern Peloponnese, Greece

Physical and Anthropogenic Factors Related to Landslide Activity in the Northern Peloponnese, Greece

A comparative Geological, Tectonic and Geomorphological assessment of the Charlotte, Regent and Madina Landslides, Western Areas, Sierra Leone

Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images

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