Regional assessment on the influence of land use related factor on landslide occurrences in Kundasang, Sabah

Sharir, Kamilia; Simon, Norbert; Roslee, Rodeano

doi:10.1063/1.4966853

Cited by 9 publications

(13 citation statements)

References 4 publications

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“…The major earthquake struck Sabah (especially Kundasang area) in June 2015 with 6.1 magnitude and hit some parts of Mount Kinabalu, which is one of the main tourist areas in Sabah. With unstable hilly slopes and considerable number of landslides (Sharir et al, 2016, Omar et al, 2016, Kundasang was considered suitable for the study. Kota Kinabalu was also included in this study as it is an urban area with high density population and could be affected by earthquake in Kundasang.…”

Section: Methodsmentioning

confidence: 99%

“…The quality of elements at risk mapping can be improved with the use of high density LIDAR data (Du et al, 2017, Kumar et al, 2013. Some common examples are population, buildings and engineering structures, economic activities, public services, utilities, and cultural and environmental features in the area potentially affected by landslides (Razak et al, 2011, van Westen et al, 2008. As a result of elements at risk mapping, the level of hazard and risk can be properly defined.…”

Section: Introductionmentioning

confidence: 99%

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Extraction of Element at Risk for Landslides Using Remote Sensing Method

Hasan

Rosle

Asmadi

et al. 2018

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

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<p><strong>Abstract.</strong> One of the most critical steps towards landslide risk analysis is the determination of element at risk. Element at risk describes any object that could potentially fail or exposed to hazards during disaster. Without quantification of element at risk information, it is difficult to estimate risk. This paper aims at developing a methodology to extract and quantity element at risk from airborne Light Detection and Ranging (LiDAR) data. The element at risk map produced was then used to construct exposure map which describes the amount of hazard for each element at risk involved. This study presented two study sites at Kundasang and Kota Kinabalu in Sabah with both areas have experienced major earthquake in June 2015. The results show that not all the features can be automatically extracted from the LiDAR data. For example, automatic extraction process could be done for building footprint and building heights, but for others such as roads and vegetation areas, a manual digitization is still needed because of the difficulties to differentiate between these features. In addition to this, there were also difficulties in identifying attribute for each feature, for example to separate between federal roads with state and unpaved roads. Therefore, for large area hazard and risk mapping, the authors suggested that an automatic process should be investigated in the future to reduce time and cost to extract important features from LiDAR data.</p>

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extraction of Element at Risk for Landslides Using Remote Sensing Method

Hasan

Rosle

Asmadi

et al. 2018

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

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“…This area is popular due to its topography and cool climate, which contributes to the crops production such as vegetables and fruits, and dairy products. Despite blessed with the serene environment, this area is susceptible to the geohazard such as soil mass movements and landslides, which were occurred in high frequency [5][6][7][8][9][10][11][12]. Located on two formations, which are Crocker Formation, and Trusmadi Formations, soil in Kundasang is known for low cohesion and high angle of internal friction values.…”

Section: Study Areamentioning

confidence: 99%

The Application of Semi Variogram and Ordinary Kriging in Determining the Cohesion and Clay Percentage Distribution in Hilly Area of Sabah, Malaysia

Taharin¹,

Roslee²

2021

IJDNE

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Ordinary Kriging (OK) is one of the geostatistical methods, which were used in the variation types of mapping, which related to the soil. Compliment by semi variogram models, OK has become one of the most sought out method for the digital mapping, which applied Geographical Information System (GIS) as a main approach. Four semi variogram models, which are spherical, exponential, circular and gaussian would be applied to determine the best model for the mapping purposes, with Root-Mean-Squared-Error (RMSE) as a performance indicator. The value of the cohesion and clay percentage will be based according to the related depth. Each semi variogram model will be applied to determine the best model for each depth, whether it is cohesion or clay percentage, and producing a map, as a result. This mapping would be an alternative to the geological mapping, whereby it would show the range of the cohesion and clay percentage values rather than soil types.

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“…Kota Kinabalu, Sabah (Figure 1) has experienced various scales of landslides. Due to demands for increasing development and residential are taking places in hillslope areas, human activities such as deforestation or excavation of slopes for road cuts and building sites have become threat and hazards to residents [1][2][3][4]. The historical data gathered shows that landslide often occurred due to several causative factors.…”

Section: Introductionmentioning

confidence: 99%

Application of Analytical Hierarchy Process (AHP) for Landslide Hazard Analysis (LHA) in Kota Kinabalu area, Sabah, Malaysia

Roslee

Sharir

Lai

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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A very good Landslide Hazard Analysis (LHA) model was developed using the Analytical Hierarchy Process (AHP) method for the area of Kota Kinabalu, Sabah. The AHP is defined as theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales that measure intangibles in relative terms. The derived priority scales are synthesised by multiplying them by the priority of their parent nodes and adding for all such nodes. Weighted value of different spatial factors from the best models calculated with the AHP method were derived. The results showed that the geology (27% variance), geodynamic features (14% variance), slope conditions (26% variance), hydrology/hydrogeology (14% variance), types of land use (3% variance), and engineering characteristics of soils (8% variance), and rocks (8% variance) play an important role in landslide susceptibility analysis. In terms of Landslide Hazard Map (LHM), the analyses resulted of Kota Kinabalu area suggests that 2.78% of the area can be categorised as Very Low Hazard, 14.14% as Low Hazard, 19.74% as Moderate Hazard, 51.63% as High Hazard, 11.34% as Very High Hazard and 0.37% as Extremely High Hazard. Model accuracy assessment of LHA was performed using consistency ratio (CR) equal to 0.0129 (< 0.1) (acceptable) and 93.50 % accuracy of the validation prediction. Thus, the newly developed method works satisfactory and high reliability; and is applicable to further research development in Kota Kinabalu, Sabah, and potentially to expand with different environmental settings.

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Regional assessment on the influence of land use related factor on landslide occurrences in Kundasang, Sabah

Cited by 9 publications

References 4 publications

Extraction of Element at Risk for Landslides Using Remote Sensing Method

Extraction of Element at Risk for Landslides Using Remote Sensing Method

The Application of Semi Variogram and Ordinary Kriging in Determining the Cohesion and Clay Percentage Distribution in Hilly Area of Sabah, Malaysia

Application of Analytical Hierarchy Process (AHP) for Landslide Hazard Analysis (LHA) in Kota Kinabalu area, Sabah, Malaysia

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