Susceptibility of existing and planned Chinese railway system subjected to rainfall-induced multi-hazards

Liu, Kai; Wang, Ming; Cao, Yuting; Zhu, Weihua; Guiling, Yang

doi:10.1016/j.tra.2018.08.030

Cited by 36 publications

(19 citation statements)

References 26 publications

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“…Machine learning methods are also available for multi-hazard risk assessment. In Reference [45], risk analysis for each natural hazard type was carried out by modifying the weights of each parameter according to the hazard type using the random forest (RF) method. Afterward, a multi-hazard map was produced by combining the results.…”

Section: Background On Multi-hazard Assessmentmentioning

confidence: 99%

Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

Yanar

Kocaman

Gökçeoğlu

2020

IJGI

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Urban areas may be affected by multiple hazards, and integrated hazard susceptibility maps are needed for suitable site selection and planning. Furthermore, geological–geotechnical parameters, construction costs, and the spatial distribution of existing infrastructure should be taken into account for this purpose. Up-to-date land-use and land-cover (LULC) maps, as well as natural hazard susceptibility maps, can be frequently obtained from high-resolution satellite sensors. In this study, an integrated hazard susceptibility assessment was performed for a developing urban settlement (Mamak District of Ankara City, Turkey) considering landslide and flood potential. The flood susceptibility map of Ankara City was produced in a previous study using modified analytical hierarchical process (M-AHP) approach. The landslide susceptibility map was produced using the logistic regression technique in this study. Sentinel-2 images were employed for generating LULC data with the random forest classification method. Topographical derivatives obtained from a high-resolution digital elevation model and lithological parameters were employed for the production of landslide susceptibility maps. For the integrated hazard susceptibility assessment, the Mamdani fuzzy algorithm was considered, and the results are discussed in the present study. The results demonstrate that multi-hazard susceptibility assessment maps for urban planning can be obtained by combining a set of expert-based and ensemble learning methods.

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Section: Background On Multi-hazard Assessmentmentioning

confidence: 99%

Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

Yanar

Kocaman

Gökçeoğlu

2020

IJGI

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“…Within the research articles, documents with quantitative analysis prevail with 57%. (Wipulanusat, Nakrod, & Prabnarong, 2009), (Mahendra, Prakash, Srinivasa Kumar, Shenoi, & Shailesh, 2010), (Lozoya, Sardá, & Jiménez, 2011), (Kappes, Keiler, von Elverfeldt, & Glade, 2012), (Kappes, Gruber, et al, 2012), (Marzocchi, Garcia-Aristizabal, Gasparini, Mastellone, & Ruocco, 2012), (Kameshwar & Padgett, 2014), (Johnson, Depietri, & Breil, 2016), (Gill & Malamud, 2017), (Stults, 2017), (Villegas-González, Ramos-Cañón, González-Méndez, González-Salazar, & De Plaza-Solórzano, 2017), (Bonacho & Oliveira, 2018), (Furlan, Torresan, Critto, & Marcomini, 2018), (Hagenlocher, Renaud, Haas, & Sebesvari, 2018), (Hernández, Carreño, & Castillo, 2018), (Kwag & Hahm, 2018), (K. Liu, Wang, Cao, Zhu, & Yang, 2018), (Mukherjee, Nateghi, & Hastak, 2018), (Pilone & Demichela, 2018), (Reniers, Khakzad, Cozzani, & Khan, 2018), (Sahoo & Bhaskaran, 2018), (Viavattene et al, 2018), (Zimmaro, Stewart, Brandenberg, Kwak, & Jongejan, 2018) As mentioned above, at the level of research articles, quantitative analyses predominate, and this is a trend that is repeated under the type of analysis level (see Figure 10). Descriptive analyses represent 23% of the 30 analyzed documents, and the other ones contain qualitative, semi-quantitative, and mixed analysis approaches (e.g., combining qualitative, semiquantitative and quantitative analyses).…”

Section: Analysis Of Publications Based On Multi-hazard Analysismentioning

confidence: 99%

Risk analysis in Natech events: State of the art

Mesa-Gómez

Casal

Muñoz

2020

Journal of Loss Prevention in the Process Industries

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“…In addition to the collapse of slopes, the geohazard in region IV.A also resulted in ground collapse caused by unreasonable drainage facilities. In these regions, slope protection and reasonable drainage facilities should be strengthened in highway construction (Chang et al 2011;Liu et al 2018). 4.…”

Section: Geohazards Regionalizationmentioning

confidence: 99%

Geohazards regionalization along highways in Shandong Province, China

Yang

Zhao

Cheng

2020

Geomatics, Natural Hazards and Risk

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The disturbance of the highway construction to the terrain and the natural environmental factors are the main causes of the geohazards along the highway. We collected geohazards along the highway in Shandong Province and put forward the comprehensive geohazard index to reflect the risk of geohazards along the highway. The index consists of an intensity index describing the development of geohazards and a sensitivity index describing the potential risk of geohazards. The article uses an incomplete additive language matrix to calculate the weight of each index and factor. Based on the Getis-Ord Gi Ã statistic tool, the spatial distribution of landslides and collapses, debris flows, ground collapses, and unstable slopes are analyzed, and the geohazard intensity index is calculated by spatial superposition. The relationship between slope gradient, rainfall, vegetation coverage, rock type and geohazards is analyzed, and the geohazard sensitivity index is calculated by spatial superposition. Based on the comprehensive geohazard index and geomorphological characteristics, Shandong Province is divided into 4 geohazard first-level regions and 11 geohazard second-level regions, providing a basis for highway planning and construction.

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Susceptibility of existing and planned Chinese railway system subjected to rainfall-induced multi-hazards

Cited by 36 publications

References 26 publications

Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

Risk analysis in Natech events: State of the art

Geohazards regionalization along highways in Shandong Province, China

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