Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (Lidar) in Densely Vegetated Areas of Tropics

Bibi, Tehmina; Razak, Khamarrul Azahari; Rahman, Alias Abdul; Latif, Aliza Abdul

doi:10.5194/isprs-archives-xlii-4-w5-21-2017

Cited by 10 publications

(7 citation statements)

References 52 publications

(51 reference statements)

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“…Landslide distribution map is used as base to assess the susceptibility of LS in intensity evaluation process of hazard (Bibi et al, 2017). Guzzetti et al 2012mentioned that still the LS inventories are prepared or assembled either continuous in time or based on causing event e.g.…”

Section: Methodsmentioning

confidence: 99%

Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area

Gul

Bibi

Rahim

et al. 2021

IJEEG

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Landslide is a frequently occurring natural calamity in the northern areas of Pakistan. The current study is aimed to assess the susceptibility of landslide hazard to highlight the vulnerable areas for the purpose of risk reduction along Neelum and Jehlum rivers in district Muzaffarabad. A data-driven predictive approach was adopted to conduct this study by using Weight of Evidence (WOE) model along with eleven conditioning factors. A spatial distribution map of landslides was prepared using orthophoto, previous records, and derivatives (hill shad, topographic openness, slope, aspect, curvature) of Digital Elevation Model (DEM). The results show that the roads, lithology, and rivers are the most important triggering factors for landslides in both valleys. Approximately 30% of the area is under low susceptibility zone in Jhelum valley while only 13% of the area falls under low susceptibility zone in Neelum river valley. In Jhelum river valley the medium susceptibility zone covers 35% of the total area whereas, Neelam river valley has 26% of the total area under medium susceptibility zone. Around 61% of the land in the Neelam river valley and 35% of the land in the Jhelum river valley are under high susceptibility zone. The area under high hazard lies in the north-east of the district due to multiple conducive factors to trigger landslides including weak lithology (mudstone, sandstone, shales, and clays), high altitude along steep slopes and excessive precipitation (1800 mm/ year). Furthermore, the high hazard zone in study area is not suitable for construction purpose but was suitable for plantation. The validation result (89.41%) is justifying the performance of this model.

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Section: Methodsmentioning

confidence: 99%

Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area

Gul

Bibi

Rahim

et al. 2021

IJEEG

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“…Compared with the geological disaster survey conducted by optical remote sensing technology, high density, high efficiency and high precision are the characteristics of airborne LiDAR measurement technology (Arnone, E., et al, 2016). Compared with traditional optical remote sensing technology, optical remote sensing technology can only obtain two-dimensional spectral feature information, and the spectral information cannot penetrate through vegetation, and it cannot be acquired at night (Bibi, T., et al ,2017). Airborne LiDAR technology can penetrate vegetation (Chang, K.-T., et al, 2007), and the terrain morphological feature information obtained is clear and realistic, which has unique advantages for the identification of landslide disasters.…”

Section: Advantages Of Early Identification Of Airborne Lidar Geologimentioning

confidence: 99%

Preliminary Results and Analyses of Post-Earthquake Geological Hazards in Jiuzhaigou Based on Airborne Lidar and Imagery

She

Zhou

Liu

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. A magnitude 7.0 earthquake struck Jiuzhaigou County, Sichuan Province at 21:00 on August 8, 2017, and the epicentre was located in the major tourist spot of Jiuzhaigou. This paper describes the surveying and mapping project of post-earthquake hazards regions for the restoration and reconstruction purposes. The earthquake triggered thousands of collapses and landslide disasters, causing severe damage to tourist land scapes and scenic roads such as Jiuzhaigou Panda Sea. The geological hazards of steep mountains and steep slopes and dense vegetation in the scenic area are highly concealed. Traditional susceptibility mapping methods for geological hazard using only airborne images have encountered great difficulties. Aiming to solve this issue, airborne LiDAR and high-resolution images were used jointly to interpret geological disasters in this area. The three-dimensional interpretation signs of disasters are established comprehensively by using optical images and digital elevation models to obtain the distribution characteristics of existing geological hazards, coseismic geological hazards and hidden dangers, which support the restoration and reconstruction of the tourist spots.

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“…The simulated result could provide important insight for improving the management of hazards and risks in this tectonically active area. Several studies have been conducted to investigate the earthquake at Kundasang [7], which have focused mainly on the causes and impacts of the earthquake [8], landslide inventory [32,33], landslide susceptibility [34], landslide hazard and risk [35], land cover assessment [36], and business continuity plan [30]. However, little is known about the debris flow travelling along the channelised Mesilau river from the upstream to the downstream areas.…”

Section: Introductionmentioning

confidence: 99%

Modelling Debris Flow Runout: A Case Study on the Mesilau Watershed, Kundasang, Sabah

Rosli

Ros

Razak

et al. 2021

Water

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Debris flows are among the fatal geological hazards in Malaysia, with 23 incidents recorded in the last two decades. To date, very few studies have been carried out to understand the debris flow processes, causes, and runouts nationwide. This study simulated the debris flow at the Mesilau watershed of Kundasang Sabah caused by the prolonged rainfall after the 2015 Ranau earthquake. Several interrelated processing platforms, such as ArcGIS, HEC-HMS, and HyperKANAKO, were used to extract the parameters, model the debris flow, and perform a sensitivity analysis to achieve the best-fit debris flow runout. The debris flow travelled at least 18.6 km to the Liwagu Dam. The best-fit runout suggested that the average velocity was 12.5 m/s and the lead time to arrive at the Mesilau village was 4.5 min. This high debris flow velocity was probably due to the high-water content from the watershed baseflow with a discharge rate of 563.8 m3/s. The flow depth and depositional thickness were both lower than 5.0 m. This study could provide crucial inputs for designing an early warning system, improving risk communication, and strengthening the local disaster risk reduction and resilience strategy in a tectonically active area in Malaysia.

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Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (Lidar) in Densely Vegetated Areas of Tropics

Cited by 10 publications

References 52 publications

Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area

Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area

Preliminary Results and Analyses of Post-Earthquake Geological Hazards in Jiuzhaigou Based on Airborne Lidar and Imagery

Modelling Debris Flow Runout: A Case Study on the Mesilau Watershed, Kundasang, Sabah

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