Geotechnical investigation and landslide susceptibility assessment along the Neelum road: a case study from Lesser Himalayas, Pakistan

Ahmed, Khawaja Shoaib; Basharat, Muhammad; Riaz, Muhammad Tayyib; Sarfraz, Yasir; Shahzad, Amir

doi:10.1007/s12517-021-07396-6

Cited by 21 publications

(13 citation statements)

References 49 publications

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“…Numerous studies were performed to generate regional-scale LSMs and proposed suitable models for the assessment of susceptibilities. Recently a review highlighted that more than 500 research articles based on 70 different models were published in 2005-2016 ; however, it is pertinent to mention here that a few studies (Ahmed et al, 2021;Basharat et al, 2016;Kamp et al, 2008) The generated LSMs of all six models are well harmonized with one another, although the ratio of LSZs with respect to area percentage distribution is different in each model (Figure 11). Generally, a uniform pattern of high and very high LSZs in all models observed along an earthquake-affected road section of Neelum Highway; however, it was noticed in field investigations that landsliding is the most common phenomenon with potential hazards along slope angles ranging from 40 to 60 and fragile lithologies that lies in the proximity to 13; Table 4).…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies were performed to generate regional scale LSMs and proposed suitable models for the assessment of susceptibilities. Recently a review highlighted that more than 500 research articles based on 70 different models were published in 2005-2016 , however it is pertinent to mention here that few studies (Ahmed et al, 2021;Basharat et al, 2016;Kamp et al, 2008) the ratio of LSZs with respect to area percentage distribution is different in each model (Fig. 11).…”

Section: Discussionmentioning

confidence: 99%

“…However, only a few studies were focused on landslide susceptibility mapping using conventional quantitative techniques such as Basharat et al (2016) and Kamp et al (2008), where those work undertook LSP for earthquake-affected areas based on semi-quantitative approach (AHP). Recently, Ahmed et al (2021) demarcated the landslide prone areas along a small portion of Neelum road using WoE method and investigated the geo-technical aspect of specific landslides. Though these studies demonstrate landslide hazard maps which were modulated by limited number of landslide conditioning factors, a comprehensive study on spatial prediction of landslide susceptibility to draw a robust conclusion about prediction ability of different data-driven techniques is still lacking for this region.…”

Section: Introductionmentioning

confidence: 99%

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Application of data‐driven techniques for landslide susceptibility prediction along an earthquake‐affected road section in Kashmir Himalaya

Gardezi¹,

Usmani

Chen

et al. 2022

Geological Journal

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of data‐driven techniques for landslide susceptibility prediction along an earthquake‐affected road section in Kashmir Himalaya

Gardezi¹,

Usmani

Chen

et al. 2022

Geological Journal

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“…An analysis can be performed on all northern areas for the measurement of landslide hazard zonation and comparison on a large spatial extent. Landslides are di cult to forecast (Ahmed et al, 2021) since they are unpredictable and can have potential consequences similar to other natural disasters such as oods, earthquakes, and avalanches.…”

Section: Discussionmentioning

confidence: 99%

Landslide hazard, susceptibility and risk assessment (HSRA) based on remote sensing and GIS data models: a case study of Muzaffarabad Pakistan

Ahmad

Shao

Aslam

et al. 2022

Stoch Environ Res Risk Assess

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The notion of this research is based on the two devastating earthquake events that happened on October 8, 2005, and September 24, 2019, in the regions of Azad Kashmir. This study aims at (i) identi cation of the susceptible zones where landslides will occur in the future; (ii) preparation of landslide inventory maps using vector data, satellite imagery, Shuttle Radar Topographic Mission (STRM) and Advanced Space-borne Thermal Emission and Re ection Radiometer (ASTER) DEM; (iii) implementation of Analytical Hierarchy Process (AHP) model using weighted overlay analysis (WOA). For this purpose, key factors such as land-use, faults, slope, contours, soil and seismology are used to develop a landslide hazard zonation map. The output landslide susceptibility map has four susceptibility levels such as low, medium, high, and very high vulnerable zones. The results indicated that a highly susceptible landslide zone is found in the northwestern part of Muzaffarabad, which is a metropolitan region. Moreover, there are 127 active landslides are identi ed and collectively about 9% of the study area is very highly susceptible to future landslides. Moreover, research ndings are helpful in tactful thinking for future infrastructure development, ecological protection in high-susceptible landslide regions in Muzaffarabad.It also allows the Government to make strategies for that speci c zones on a priority basis to reduce the casualties and destruction in future landslide events.

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“…5 points, Nusaniwe District 3 points and South Leitimur District 1 point. In 2019 there were 32 landslides and landslides that spread across five sub-districts, while in 2020, 163 landslides were found in the Ambon City area (Ahmad, 2022); (Ahmed et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Study of Physical and Mineral Properties of Soil Clay Landslide Location of IAIN Campus Ambon City

Luhukay

Risamasu²,

Osok³

et al. 2022

IJMABER

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This study aims to determine physical and clay mineral properties of soils and how they affect the occurrence of erosion in the IAIN Campus Ambon. The results indicated that the two soil profiles shows a variety in soil properties. the largest distribution of soil particle density is 2.63 at soil layer P2L3 and the smallest is 2.26 at P1L1, the largest soil pore distribution is 60.12% at P2L1 and the smallest is 29.36% at P1L3, while the largest soil pores ratio distribution is 1.51% at P2L1 and the smallest is 0.42% at soil layer P1L3. The soil porosity reflects the level of the soil ability to pass water flow (permeability) or the speed of water flow to pass through the soil mass (percolation). By the decreasing of soil porosity and pore ratio in layers 3 and 4, the permeability is also slower. The major clay mineral found in both soil profiles is kaolinite, an unwell consolidated secondary clay mineral type 1:1 mixed with quartz, the most weathering resistant primary minerals. These two minerals have lower friction resistance due to the increasing of clay content in the lower soil profiles. The physical and hydrological soil properties as well as the presence of kaolinite and quartz in the lower soil layers are considered to be the cause of the erosion occurrence in the study area (IAIN campus).

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Geotechnical investigation and landslide susceptibility assessment along the Neelum road: a case study from Lesser Himalayas, Pakistan

Cited by 21 publications

References 49 publications

Application of data‐driven techniques for landslide susceptibility prediction along an earthquake‐affected road section in Kashmir Himalaya

Application of data‐driven techniques for landslide susceptibility prediction along an earthquake‐affected road section in Kashmir Himalaya

Landslide hazard, susceptibility and risk assessment (HSRA) based on remote sensing and GIS data models: a case study of Muzaffarabad Pakistan

Study of Physical and Mineral Properties of Soil Clay Landslide Location of IAIN Campus Ambon City

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