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This study assesses the influence of development on landslide occurrences in a rapidly developing area, Kota Kinabalu in Sabah Malaysia, across three assessment years (1978, 1994 and 2010). Two development indicators, land use and road density, were used to measure the influence of development on landslide occurrence. Land use was classified into f...
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... were digitized as vector features and computed as a road density map based on Eyles et al.'s (1978) method of length per unit area. This method relies on the use of a grid placed over the area of interest ( Figure 3). Generated using the Fishnet tool in ArcGIS 9.3, a grid of 200 m × 200 m captured almost all slope failures related to road cuts and excludes landslides unrelated to road cuts, such as landslides which occurred in resi- dential areas and naturally occurring landslides. ...
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Citations
... When the spatial relationship is robust, the ratio value equals or exceeds one, whereas a weaker relationship yields a ratio value below one. Measurable, the Frequency Ratio denotes the probability ratio between the presence and absence of landslide incidents [1,[5][6][7][8]. The outcome of the Frequency Ratio assessments manifests in the formulation of the Landslide Hazard Index [1] or the Landslide Susceptibility Index [2,3], amalgamating individual factors' Frequency Ratio values. ...
... The merits of the Frequency Ratio model are manifold, prominently its streamlined data processing. Noted for its simplicity, comprehensibility, and expeditiousness [1], this model thrives in the Geographic Information System (GIS) environment, deftly managing the copious Frequency Ratio data and simplifying analysis [3][4][5][6][7]. The outcomes yielded by this model are readily intelligible and amenable to efficient management [3][4][5][6][7]. ...
... Noted for its simplicity, comprehensibility, and expeditiousness [1], this model thrives in the Geographic Information System (GIS) environment, deftly managing the copious Frequency Ratio data and simplifying analysis [3][4][5][6][7]. The outcomes yielded by this model are readily intelligible and amenable to efficient management [3][4][5][6][7]. ...
... Direct runoff increases when impermeable surfaces replace vegetation. It also leads to increased soil erosion and sediment transport that accumulate at the base of steep hillslopes, thus increasing the likelihood of debris flow occurring in due time (Simon et al. 2015). Among the five rivers, it was reported that the earthquake most impacted the Penataran River. ...
Background
Earthquake is one of the most destructive natural disasters, which cause immediate and long-term changes to the river systems. This research aimed to examine the immediate and five-year impacts of the 2015 Ranau Earthquake (6.0 Mw) on river systems in Malaysian state of Sabah, a region of low earthquake hazard.
Methods
We used object-based classification on Landsat 8 (2014 and 2015) and Sentinel-2A (2020) satellite imageries to derive land cover time series for investigating the impacts on the riparian areas.
Results
The earthquake removed vegetation in the riparian zones of four rivers, the highest being the Penataran River (69.21 ha). During the immediate impact period (2014–2015), river bar formation occurred in all rivers, with the largest increase occurring in the Kadamaian River (56.97 ha), followed by the Panataran River (54.36 ha), which had no river bar before the earthquake. The river bar of the Kadamaian River continued to increase, whereas the river bar of the Panataran River decreased five years after the earthquake. Land cover transition analysis revealed that 78.39 ha of vegetation, barren land, and river water areas changed to river bars in the Kadamaian riparian area during the immediate impact period. Except for 26.87% of river bars in the Kadamaian riparian area in 2015, most river bars transitioned to other land cover types five years later. During the period of immediate impact, 22.05 ha of vegetation and 10.71 ha of river water were transformed into river bars along the Penataran River. Five years later, except for 16.2 ha, all river bar areas had transitioned to other cover types. Additionally, 17.7 ha of new river bars were formed. This study provides crucial data on post-earthquake land cover changes, particularly river bar formation and changes, for assessing the earthquake impacts on the river systems and supporting impact mitigation.
... Although land-use changes do influence landslide susceptibility, this influence depends on the local topographic, lithologic, and hydrologic conditions as well as on the rate of land-use changes (Soma and Kubota 2017;Chen et al. 2019). Previous studies (Braun et al. 2019;Simon et al. 2015) indicated that changes in landslide susceptibility may increase with the rate of urban expansion and depend on population and road density. Although landslide susceptibility has been shown to generally increase with the degree and rate of urbanization, studies have previously used only landslide inventories that were mapped in areas and times of urban expansion and thus primarily explored the immediate effect of urbanization on Landslides landslide susceptibility (Alexander 1986;Smyth and Royle 2000;Sassa et al. 2004;Cascini et al. 2005;Dragićević et al. 2015;Frodella et al. 2018;Lee et al. 2018). ...
... Comparison of our results to studies that examined the influence of recent urbanization on landslide susceptibility reveals both similarities and differences. Studies that focused on recent urbanization (Dragićević et al. 2015;Simon et al. 2015;Frodella et al. 2018;Braun et al. 2019) report similar results to ours in that landslide estimates between urbanized and non-urbanized areas have low spatial correlation. Our results indicate that, in both urbanized and non-urbanized areas within our study area, the influence of aspect and stratigraphic formation are higher compared to other study areas. ...
... A major difference between this study and previous studies is the low ranking of the land cover factor in all four models, whereas in prior studies landcover is typically highly ranked (Kumar and Bhagavanulu 2008;Kafy et al. 2017;Pisano et al. 2017;Avila et al. 2021). This may reflect the difference between the effect of decades-old urbanization (this study) versus recent urbanization (Dragićević et al. 2015;Simon et al. 2015;Frodella et al. 2018;Braun et al. 2019) and indicates that the relative influence of land cover on landslide susceptibility may decrease through time. However, this may also reflect differences in environmental and/or climatic conditions and in land-cover categories between this and previous studies. ...
Landslides pose a threat to life and infrastructure and are influenced by anthropogenic modifications associated with land development. These modifications can affect susceptibility to landslides, and thus quantifying their influence on landslide occurrence can help design sustainable development efforts. Although landslide susceptibility has been shown to increase following urban expansion, the long-lasting effect of urbanization on landslide susceptibility remains largely unquantified. Hence, susceptibility maps developed based on inventories from non-urbanized areas may incorrectly evaluate the hazard in urbanized areas. To quantify this effect, we analyzed a landslide inventory from southwestern Pennsylvania, where the pulse of urbanization occurred more than a decade before the inventory was created. Using road density as a proxy for urbanization, the study area was divided into urbanized and non-urbanized areas. Susceptibility patterns were computed using statistical analyses of a post-urbanization landslide inventory together with maps of topographic, land cover, and geologic factors. A pre-urbanization landslide inventory was used as a control. Our findings indicate that urbanization has a decades-long effect on landslide susceptibility, where urbanized areas are generally more susceptible to landslides. In urbanized areas landslides are strongly associated with distance from roads and topographic curvature, whereas in non-urbanized landslides are strongly associated with stratigraphic formation and distance from streams. The consistent differences in susceptibility patterns between urbanized and non-urbanized areas indicate that urbanization has a long-lasting effect on landslide susceptibility and that susceptibility estimates should be made separately for these different environments to account for the persistent influence of urbanization.
... The road network is often associated with an increase in landslide events (Skilodimou et al. 2018). Meanwhile, road density is often used to measure the effect of development on landslide formation and distribution (Simon et al. 2015). Distance from the road represents a negative relation with landslide events (Akgün and Bulut 2007). ...
Landslide is a severe geohazard in many mountainous areas of Vietnam during the rainy season. They directly threaten human lives and properties every year. Landslide susceptibility maps are useful tools for risk mitigation, land-use planning, and early warning systems for local areas. It is necessary to update these maps continuously because of the complexity of landslide events. This fact requires further extending the approach techniques with practical implications. Therefore, this study aimed to develop landslide susceptibility prediction maps based on advanced machine learning (ML) techniques. Five state-of-the-art hybrid ML models were developed: bagging MLP, dagging MLP, decorate MLP, rotation forest MLP, and random subspace MLP with multilayer perceptron (MLP) as a base classifier. Sixteen causative factors were collected to build landslide susceptibility maps based on the relationship between historical landslide locations and specific local geo-environmental conditions. The model performance was verified using various statistical indexes. Based on the area under ROC curve (AUC) analysis results of the testing dataset, the rotation forest MLP model has the greatest predictive accuracy of AUC = 0.818. It is followed by the decorate MLP and bagging MLP (AUC = 0.804), the random subspace MLP model (AUC = 0.796), the dagging MLP (AUC = 0.789), and the single MLP (AUC = 0.698). The results of this study can be applied effectively to other mountainous regions to mitigate the risk of landslides.
... The road network is often associated with an increase in landslide events (Skilodimou et al. 2018). Meanwhile, road density is often used to measure the effect of development on landslide formation and distribution (Simon et al. 2015). Distance from the road represents a negative relation with landslide events (Akgün and Bulut 2007). ...
Landslides are a serious geohazard in many mountainous areas of Vietnam during the rainy season. They directly threaten human lives and properties every year. Landslide susceptibility maps are useful tools for risk mitigation, land-use planning, and early warning systems for local areas. It is necessary to update these maps continuously because of the complexity of landslide events. This fact requires further extending the approach techniques with practical implications. Therefore, this study aimed to develop landslide susceptibility prediction maps based on advanced Machine Learning (ML) techniques. Five state-of-art hybrid ML models were developed: Bagging – MLP, Dagging – MLP, Decorate – MLP, Rotation Forest – MLP, Random SubSpace – MLP with Multi-Layer Perceptron (MLP) as a base classifier. Sixteen causative factors were collected to build landslide susceptibility maps based on the relationship between historical landslide locations and specific local geo-environmental conditions. The model performance was verified using various statistical indexes. Based on the Area Under ROC curve (AUC) analysis results of the testing dataset, the Rotation Forest – MLP model has the greatest predictive accuracy of AUC = 0.818. It is followed by the Decorate – MLP and Bagging – MLP (AUC=0.804), the Random SubSpace – MLP model (AUC=0.796), the Dagging – MLP (AUC=0.789), and the single MLP (AUC=0.698). The results of this study can be applied effectively to other mountainous regions to mitigate the risk of landslides.
... Slope failure associated with steep slopes and heavy rain (runoff) is one of the outcomes which plagues roads in Malaysia especially in Sabah since most of the time, the geological inputs were rarely considered during the design stage and construction execution in accordance to the references [2][3][4][5][6][7]. Hence, it is now a common practice to submit both Urban Storm (MSMA) and ESCP calculation for most infrastructure works. ...
At present, most academics and practitioners only make assumptions or simplistic correlation between soils in Sabah, Malaysia and soils in West Malaysia in order determine the Soil Erodibility Factor for Erosion and Sedimentation Control Plan (ESCP) submission apart from using The Soils of Sabah, Volume 5 which is rather archaic or obsolete. This study shall be the foundation for moves to build up databank for Department and Irrigation Drainage (DID) Sabah, Malaysia based on soil taxonomy for erosion and sedimentation control calculations. In term of environmental control application, this research provides specific required information in order to generate precise calculation in projecting the total sediment yield for ESCP for areas around the West Coast of Sabah. Findings of the study would benefit both academicians and ESCP practitioners in generating sediment yield based on Soil Map of Sabah.
... He used the frequency ratio coefficients of the hydrological factor to produce map. On the other hand (Simon et al. 2015) assessed the influence of development on land slide occurrence using 3 years' time series, based on two indicators; land use and road density and showed a positive relationship with each of the factors. (Jebur et al. 2015) who conducted research at Gunung pass, detected a vertical slope movement, which was highly vegetated tropical area. ...
... The literature study revealed that less research studies were conducted on quantification of the strength of limestone. The local researchers were focused on rock mass classification [8], landslide [9], [10] and [11], rock fall [12] and prediction of uniaxial compressive strength using ultrasonic [13], [14], [15] and [16]. However, [17] investigated the influenced of conditions of weathering to the geomechanical strength of Granites and Schists. ...
The geomechanical strength of rock materials plays a significant role in influencing the stability of both cut rock slopes and underground openings. The strength characteristics are influenced by both material characteristics and the condition of weathering. This paper presents a systematic approach to quantify the rock material strength characteristics for material failure and material & discontinuities failure by using uniaxial compressive strength, point load strength index and Brazilian tensile strength for carbonate rocks. The mean value of compressive strength, point load strength index and Brazilian tensile strength for with material failure and material & discontinuities failure were 76.8±4.5 and 41.2±4.1 MPa respectively. The Point load strength index for material failure and material & discontinuities failure were 3.1 ± 0.2 MPa and 1.8 ± 0.3 MPa respectively. The Brazilian tensile strength with material failure and material & discontinuities failure were7.1 ± 0.3 MPa and 4.1 ± 0.3 MPa respectively. The results of this research revealed that the geomechanical strengths of rock material of carbonate rocks for material & discontinuities failure deteriorates approximately ½ from material failure.
... The literature study revealed that less research studies have been conducted on limestone hillslope stability assessment. The local researchers were focused on rock mass classification, landslides, rock fall and prediction of uniaxial compressive strength using ultrasonic velocities [2][3][4][5][6][7][8][9][10]. Some researcher characterized the discontinuity surface roughness by establishing a polynomial relationship between JRC with peak friction angles schist and granite [11][12][13]. ...
The uniqueness of the karst topography of Kinta Valley is the result of the spectacular shaped steep-sided
limestone towers. The instability of these hillslopes however, may affect the vulnerability of the surrounding
area. This paper presents the results of slope stability assessment by using kinematic analysis to investigate the
possible failure modes of 7 slopes in Gua Naga Mas (GNM1, GNM2 and GNM3), Gua Kandu (GK1, GK2 and GK3)
and Gua Tempurung (GT) located in the southern part of the Kinta Valley, Ipoh, Perak. From the results of the
slope stability assessment, it was determined that planar failure and wedge failure were the main failure modes.
The GNM1 slope of Gua Naga Mas consist of four wedge failures and a planar failure with dip directions/dip
angles of 005⁰/54⁰, 354⁰/59⁰, 124⁰/52⁰, 360⁰/50⁰ and 063⁰/70⁰ respectively. The GNM2 slope consists of a
wedge failure with the dip direction/dip angle of 021⁰/64⁰. Two wedge failures and a planar failure were
identified on slope GNM3 with the respective dip directions/dip angles of 336⁰/49⁰, 301⁰/68⁰ and 270⁰/71⁰.
The GK1 slope for Gua Kandu consists of wedge and planar failures with dip directions/dip angles of 231⁰/49⁰
and 217⁰/49⁰ respectively. The mode of failure at GK2 slope was identified as wedge failure with the dip
direction/dip angle of 154⁰/44⁰. No mode of failure was identified on slope of GK3. Slope GT of Gua Tempurung
was identified to have two wedge failures with dip directions/dip angles of 011⁰/49⁰ and 321⁰/48⁰ respectively.
... The literature study showed that less research were conducted on the peak shear strength of discontinuity surfaces of limestone. Local researchers focused more on rock mass classification (Norbert et al. 2016), landslide study (Norbert et al. 2015aNorbert et al. , 2014Norbert et al. , 2013), rock fall study (Norbert et al. 2015b) and prediction of uniaxial compressive strength (Goh et al. 2016Goh et al. , 2015aGoh et al. , 2015bGoh et al. , 2014b). However, GhaniRafek et al. ( , 2011) andGoh et al. (2012Goh et al. ( , 2014a) established a polynomial relationship between JRC with peak friction angles for schist and granite. ...
The peak friction angle (φpeak) roughness of discontinuity surfaces is a value that is fundamental to the understanding of shear strength of geological discontinuities, considering its importance in determining the mechanical properties of the discontinuity surface. It is however, both time and cost demanding to determine the peak friction angle as it requires an extensive series of laboratory tests. This paper presents an approach in the form of an experimentally determined polynomial equation to estimate peak friction angle of limestone discontinuity surfaces by measuring the Joint Roughness Coefficient (JRC) values in a field survey study, and applying the fore mentioned empirical correlation. A total of 1967 tilt tests and JRC measurements were conducted in the laboratory to determine the peak friction angles of rough limestone discontinuity surfaces. The experimental results were analyzed and correlated to establish a polynomial equation of φpeak = -0.0635JRC2 + 3.95JRC + 25.2 with coefficient of determination (R2) of 0.99. The laboratory results were also compared with theoretical results calculated from Barton's linear equation. The results shown that estimation of peak friction angles were more accurate using the newly proposed polynomial equation since the percentage differences between measured and calculated peak friction angles is less than 6% compared to estimation from Barton's linear equation where the percentage of differences is less than 11%. The proposed correlation offers a practical method for estimation of peak friction angles of discontinuity surfaces of limestone from measurement of JRC in the field.
