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Development of a hybrid methodology for the susceptibility and hazard analysis o...

Development of a hybrid methodology for the susceptibility and hazard analysis of landslides The activation as well as the consequences of natural geohazards, such as landslides, are difficult to predict, as they depend on factors characterized by large uncertainties, such as the geological and geotechnical conditions, an... see more

09/05/2024

GEOIMAGING LIMITED

158K€

Project Budget: 158K€

Project leader

GEOIMAGING LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo H2020 notifico la concesión del proyecto The day 2024-05-09

MSCA-IF-2020: Individual Fellowships Objective:The goal of the Individual Fellowships is to enhance the creative and innovative potential...

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2 Participantes

GEOIMAGING LIMITED

157.94K€ | Leader

GEOFEM LIMITED

N.D. | participant

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Project duration: 36 months Date Start: 2021-04-20
End date: 2024-05-09

Project leader

GEOIMAGING LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 158K€

participation deadline Sin fecha límite de participación.

Project description The activation as well as the consequences of natural geohazards, such as landslides, are difficult to predict, as they depend on factors characterized by large uncertainties, such as the geological and geotechnical conditions, and the influence of human activities. The proposed study aims at the development of a novel, reliable and comprehensive method for the estimation of the landslide susceptibility and hazard. The individual goals of this study are: a) to investigate the failure mechanism of landslides and their spatio-temporal spread using an approach which combines the Earth Observation technology with the classical geotechnical research, b) to formulate an effective multimodal determinist approach for landslide susceptibility assessment, c) to develop a landslide susceptibility and hazard assessment method based on Machine Learning, d) to combine the two previous methods, effectively creating a novel, highly performing methodological approach. The new method will be able to manage more effectively the uncertainties, giving reliable results even in areas where there is scarcity of landslide records. The testbed area for the development of the new approach will be southwestern Cyprus, a region with very high density of landslide phenomena due its particular geology and relatively high seismicity. The produced hazard maps will allow the identification of areas which are susceptible to landslides and, consequently, the results of this research will help the decision-makers in taking actions towards protecting the built environment from the landslide hazards, thus securing sustainable development. Eventually, after the validation of the new method and produced maps, this process can be applied in other parts of Europe suffering from similar phenomena.

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