Coastal zones are fragile and dynamic environments, most of the time largely urbanized and particularly vulnerable to natural hazards. Therefore, coastal areas are often exposed to high risk and shoreline position monitoring and modelling is required to mitigate it. In this context, satellite data are fundamental to provide synoptic and multitemporal information useful to map and model shoreline position through time. The aim of this work was to study the shoreline evolution of two selected areas, in Portugal and in Italy. Shoreline historical rates were obtained by analyzing Landsat images from mid-80's up to 2011. Subsequently, short-term scenarios (2014) were predicted and their accuracy was assessed by comparing 2014 modelled and observed shoreline positions. After that, Landsat 8 and Sentinel 1 images were exploited to extract and compare 2015 shoreline positions in a Data Fusion context. Finally, results were interpreted for their implications in the coastal risk reduction framework.
Cenci, L., Persichillo, M.G., Disperati, L., Oliveira, E.R., Alves, F.L., Pulvirenti, L., et al. (2015). Remote sensing for coastal risk reduction purposes: optical and microwave data fusion for shoreline evolution monitoring and modelling. In International Geoscience and Remote Sensing Symposium (IGARSS) (pp.1417-1420). New York : Institute of Electrical and Electronics Engineers Inc. [10.1109/IGARSS.2015.7326043].
Remote sensing for coastal risk reduction purposes: optical and microwave data fusion for shoreline evolution monitoring and modelling
Disperati, LeonardoMembro del Collaboration Group
;
2015-01-01
Abstract
Coastal zones are fragile and dynamic environments, most of the time largely urbanized and particularly vulnerable to natural hazards. Therefore, coastal areas are often exposed to high risk and shoreline position monitoring and modelling is required to mitigate it. In this context, satellite data are fundamental to provide synoptic and multitemporal information useful to map and model shoreline position through time. The aim of this work was to study the shoreline evolution of two selected areas, in Portugal and in Italy. Shoreline historical rates were obtained by analyzing Landsat images from mid-80's up to 2011. Subsequently, short-term scenarios (2014) were predicted and their accuracy was assessed by comparing 2014 modelled and observed shoreline positions. After that, Landsat 8 and Sentinel 1 images were exploited to extract and compare 2015 shoreline positions in a Data Fusion context. Finally, results were interpreted for their implications in the coastal risk reduction framework.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1039971