Terrestrial Laser Scanner surveys performed in coastal area have generated 3D cloud points used to obtain digital elevation model and standard deviation of the micro-topography of coastal surfaces. Starting from data collected, roughness. coefficients have been estimated for each surface typology characterizing the coastal area (sand calcarenite, vegetation, etc). Applying Machine Learning techniques on digital images, the extension and the surface typology of these areas have been obtained. All data collected have been elaborated by means of software implemented stalling from known hydrodynamic formula to evaluate the inland penetration of a hypothesized tsunami
International audienceThe Alboran Basin may be subject to tsunami hazards. If such an event were to ...
We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi t...
This paper describes the examination of three practical tsunami run-up models that can be used to as...
The estimation of the inundation limit of a tsunami wave is, among other factors, influenced by coas...
Whatever the generating mechanism of a tsunami may be, this event can discharge destructive energy a...
This research aims to develop a tsunami vulnerability assessment model on land use and land cover us...
The Maddalena Peninsula coastline (south-eastern Sicily, Italy) is characterised by the occurrence o...
This study aims to develop a software framework for modeling of tsunami vulnerability using DEM and ...
This work shows the application and the validation of a procedure with the GIS GRASS to realize tsun...
The presence of mega-boulders scattered landward along gently sloping rocky coasts is attributed to...
We have studied the inland disastrous evidences of the tsunami triggered by the earthquake (M 9.0) o...
The coastline of the Maddalena peninsula (south-eastern Sicily, Italy) is characterised by the occur...
A method for rapid detection of tsunami devastated areas using multi-temporal TerraSAR-X data is pro...
Machine Learning (ML) techniques are now being used very successfully in predicting and supporting d...
Beach morphological classification was mainly established for Australian and American microtidal san...
International audienceThe Alboran Basin may be subject to tsunami hazards. If such an event were to ...
We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi t...
This paper describes the examination of three practical tsunami run-up models that can be used to as...
The estimation of the inundation limit of a tsunami wave is, among other factors, influenced by coas...
Whatever the generating mechanism of a tsunami may be, this event can discharge destructive energy a...
This research aims to develop a tsunami vulnerability assessment model on land use and land cover us...
The Maddalena Peninsula coastline (south-eastern Sicily, Italy) is characterised by the occurrence o...
This study aims to develop a software framework for modeling of tsunami vulnerability using DEM and ...
This work shows the application and the validation of a procedure with the GIS GRASS to realize tsun...
The presence of mega-boulders scattered landward along gently sloping rocky coasts is attributed to...
We have studied the inland disastrous evidences of the tsunami triggered by the earthquake (M 9.0) o...
The coastline of the Maddalena peninsula (south-eastern Sicily, Italy) is characterised by the occur...
A method for rapid detection of tsunami devastated areas using multi-temporal TerraSAR-X data is pro...
Machine Learning (ML) techniques are now being used very successfully in predicting and supporting d...
Beach morphological classification was mainly established for Australian and American microtidal san...
International audienceThe Alboran Basin may be subject to tsunami hazards. If such an event were to ...
We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi t...
This paper describes the examination of three practical tsunami run-up models that can be used to as...