Coseismic landslide susceptibility assessment using geographic information system

Saputra, Aditya; Gomez, Christopher; Hadmoko, Danang Sri; Sartohadi, Junun

doi:10.1186/s40677-016-0059-4

Cited by 12 publications

(18 citation statements)

References 34 publications

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“…Additionally, the direct measurement data of groundwater which was obtained from household well measurement, and few of borehole and geo-electric data were used to support the analysis of groundwater condition in the middle part of the study area. The analysis of coseismic landslide used mainly rainfall data from several weather stations surrounding study area, 1: 25,000 topographic map, and detailed geology map which was obtained from remote sensing interpretation and fieldwork observation by [13][14].…”

Section: Datamentioning

confidence: 99%

“…The coseismic landslide susceptibility analysis on this multi-hazard and risk study used the result of previous research conducted by [14]. This study applied method which was proposed by [17].…”

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

“…The contour map resolution is about 12.5 m. Meanwhile, the geology map scale is 1: 100,000. [14] had been conducted some remote sensing interpretation and fieldwork observation to increase the scale of geology map and produced more detailed geology and lithology information. The other parameters such as natural humidity of soil and rainfall intensity were derived from monthly average rainfall and annual rainfall intensity, respectively.…”

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

“…The other parameters such as natural humidity of soil and rainfall intensity were derived from monthly average rainfall and annual rainfall intensity, respectively. The detailed work step of coseismic landslide assessment which was conducted by [14] is provided in Figure 5 below.…”

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

“…Based on the [13][14], the study area could be classified into four Coseismic Landslide Susceptibility Level (CLSL) namely, negligible, low, moderate and medium CLSL. The negligible zone is the safest area in the study area.…”

Section: Coseismic Landslidementioning

confidence: 99%

See 4 more Smart Citations

Earthquake Triggered Multi-Hazard and Risk Study Based on Remote Sensing and Geographic Information System

Saputra¹,

Gomez²,

Delikostidis³

et al. 2018

Preprint

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Yogyakarta City is one of the big city which is located in Java Island, Indonesia. Yogyakarta City, including study area (Pleret Sub District), are very prone to earthquake hazards, because close to several active earthquake sources. For example, Sunda Megathrust which often generates a big earthquake which can affect the study area. The Sunda Megathrust extends from north to south and west to east along the Sumatra and Java Islands. Furthermore, an active normal fault called as Opak Fault pass through right in the middle of Study area and divides the study area into east and west zone. Recently, after the devastating earthquake in 2006, the population of the study area increases significantly. As a result, the housing demand is also increasing. However, due to the absence of earthquake building code in the study area, locals tend to build improper new houses. Furthermore, in some part of the mountainous area in the study area, there are some building found in unstable slopes area. Due to this condition, the multi-hazard and risk study needs to be done in Pleret. The increasing of population and improper houses in Pleret Sub-District can lead to amplify the impact. Thus, the main objective of this study is to assess the multi-hazards and risk of earthquake and other related secondary hazards such as ground amplification, liquefaction, and coseismic landslide.  The method mainly utilised the geographic information system, remote sensing and was fit up by the outcrop study. The results show that the middle part of the study area has a complex geological structure. It was indicated by a lot of unchartered faults was found in the outcrops. Furthermore, the relatively prone areas to earthquake can be determined. In term of the coseismic landslide, the prone area to the coseismic landslide is located in the east part of the study area in the middle slope of Baturagung Escarpment. The highly potential area of liquefaction is dominated in the central part of the study area. In term of building collapsed probability, the result shows that the safest house based on statistical analysis is the residential house with the building attribute of wood structure, roof cast material, distance more than 15 km from the earthquake source, and located above the Nglanggran Formation. Finally, the multi-hazard and risk analysis show that the middle part of the study area is more vulnerable than the other part of Pleret Sub-District.

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Section: Datamentioning

confidence: 99%

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

Section: The Coseismic Landslide Assessmentmentioning

confidence: 99%

Section: Coseismic Landslidementioning

confidence: 99%

See 3 more Smart Citations

Earthquake Triggered Multi-Hazard and Risk Study Based on Remote Sensing and Geographic Information System

Saputra¹,

Gomez²,

Delikostidis³

et al. 2018

Preprint

Self Cite

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Assessment of co-seismic landslide susceptibility using LR and ANCOVA in Barpak region, Nepal

2018

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Nepal was affected by a catastrophic earthquake with Mw 7.8 on 25th April, 2015 with its epicenter in the central part of Barpak village. A number of co-seismic landslides were triggered by the main shock of the event and associated aftershocks. Due to the rugged topography and vicinity of the main shock, the village was extremely affected by co-seismic landslides. In total, 59 landslides were identified using Google Earth and were verified during the field survey in Barpak village. Furthermore, 11 conditioning factors, including Peak ground acceleration (PGA), epicenter proximity, fault proximity, geology, slope, elevation, plan curvature, profile curvature, topographic wetness index, drainage proximity and the sediment transport index were selected as independent variables for analysis. In this study, logistic regression (LR) and analysis of covariance (ANCOVA) models were used and their performance was assessed. Finally, the landslide susceptibility classes were produced and an evaluation of models was done by using receiver operating characteristic curves. The area under the curve for LR and ANCOVA showed 85.38 and 78.4% accuracy, respectively. Based on the overall assessments, the LR model was more accurate than the ANCOVA model for co-seismic landslide prediction in the study area. The result of this study can be used to mitigate landslide-induced hazards and for land-use planning.

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Landslide susceptibility assessment and their disastrous impact on Makkah Al-Mukarramah urban Expansion, Saudi Arabia, using microtremor measurements

Abdelrahman

Al-Otaibi

Ibrahim

et al. 2021

Journal of King Saud University - Science

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Coseismic landslide susceptibility assessment using geographic information system

Cited by 12 publications

References 34 publications

Earthquake Triggered Multi-Hazard and Risk Study Based on Remote Sensing and Geographic Information System

Earthquake Triggered Multi-Hazard and Risk Study Based on Remote Sensing and Geographic Information System

Assessment of co-seismic landslide susceptibility using LR and ANCOVA in Barpak region, Nepal

Landslide susceptibility assessment and their disastrous impact on Makkah Al-Mukarramah urban Expansion, Saudi Arabia, using microtremor measurements

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