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Y.Y Ngai

Bio: Y.Y Ngai is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Risk assessment & Landslide. The author has an hindex of 1, co-authored 1 publications receiving 963 citations.

Papers
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Journal ArticleDOI
TL;DR: A framework for landslide risk assessment and management by which landslide risk can be reduced is proposed, and a critical review of the current state of research on assessing the probability of landsliding, runout behavior, and vulnerability is reviewed.

1,135 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, the authors review the problem of attempting to quantify landslide risk over larger areas, discussing a number of difficulties related to the generation of landslide inventory maps including information on date, type and volume of the landslide, the determination of its spatial and temporal probability, the modelling of runout and the assessment of landslide vulnerability.
Abstract: The quantification of risk has gained importance in many disciplines, including landslide studies. The literature on landslide risk assessment illustrates the developments which have taken place in the last decade and that quantitative risk assessment is feasible for geotechnical engineering on a site investigation scale and the evaluation of linear features (e.g., pipelines, roads). However, the generation of quantitative risk zonation maps for regulatory and development planning by local authorities still seems a step too far, especially at medium scales (1:10,000–1:50,000). This paper reviews the problem of attempting to quantify landslide risk over larger areas, discussing a number of difficulties related to the generation of landslide inventory maps including information on date, type and volume of the landslide, the determination of its spatial and temporal probability, the modelling of runout and the assessment of landslide vulnerability. An overview of recent developments in the different approaches to landslide hazard and risk zonation at medium scales is given. The paper concludes with a number of new advances and challenges for the future, such as the use of very detailed topographic data, the generation of event-based landslide inventory maps, the use of these maps in spatial-temporal probabilistic modelling and the use of land use and climatic change scenarios in deterministic modelling.

1,034 citations

Journal ArticleDOI
TL;DR: In this article, the authors present recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results.
Abstract: This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

776 citations

Journal ArticleDOI
Ali Yalcin1
01 Jan 2008-Catena
TL;DR: In this article, the analytical hierarchy process (AHP), the statistical index (Wi), and weighting factor (Wf) methods were used to produce and later compare three susceptibility maps.
Abstract: The Ardesen area is prone to landslides because of the climate conditions, geologic, and geomorphologic characteristics of the region. As in previous years, in 2001 due to heavy rainfall there were many landslides resulting in damage and human casualties. There is still a great danger of further landslides in the region. Therefore, it is vitally important to prepare a landslide susceptibility map of the region. In this study, the analytical hierarchy process (AHP), the statistical index (Wi), and weighting factor (Wf) methods were used to produce and later compare three susceptibility maps. For this purpose, thematic layers including landslide inventory, lithology-weathering, slope, aspect, land cover, distance to stream, drainage density, and distance to road were used. In this study area, 98% of landslides occurred in highly or completely weathered units. Lithology-weathering, land cover, and slope data layers were found to be important factors in the study area. To confirm the practicality of the three susceptibility maps were compared with a landslide activity map containing 16 active landslide zones. The outcome was that the active landslide zones do not completely fit into the high and very high susceptibility classes. But 81.3% of these landslide zones fall into the high and very high susceptibility zones of the AHP method while this is 62.5% in the case of Wi method, and 68.8% with the Wf method. In spite of the results obtained in this study, the development of a susceptibility map is usually determined by the needs and available resources. The results showed that the AHP method gave a more realistic picture of the actual distribution of landslide susceptibility, than the Wi and Wf methods.

734 citations

Journal ArticleDOI
TL;DR: A comparison of traditional statistical and novel machine learning models applied for regional scale landslide susceptibility modeling is presented and it is suggested that the framework of this model evaluation approach can be applied to assist in selection of a suitable landslide susceptibility modeled technique.

515 citations

Journal ArticleDOI
TL;DR: The aim of this contribution is to give an outline of the challenges each step of a multi-hazard (risk) analysis poses and to present current studies and approaches that face these difficulties.
Abstract: Many areas of the world are prone to several natural hazards, and effective risk reduction is only possible if all relevant threats are considered and analyzed. However, in contrast to single-hazard analyses, the examination of multiple hazards poses a range of additional challenges due to the differing characteristics of processes. This refers to the assessment of the hazard level, as well as to the vulnerability toward distinct processes, and to the arising risk level. As comparability of the single-hazard results is strongly needed, an equivalent approach has to be chosen that allows to estimate the overall hazard and consequent risk level as well as to rank threats. In addition, the visualization of a range of natural hazards or risks is a challenging task since the high quantity of information has to be depicted in a way that allows for easy and clear interpretation. The aim of this contribution is to give an outline of the challenges each step of a multi-hazard (risk) analysis poses and to present current studies and approaches that face these difficulties.

488 citations