In the past years, several studies have shown that Earth Observation (EO) data can be successfully used for analysing shoreline evolution trends and assessing coastal erosion hazard/risk. Within this framework, the exploitation of long-term archives of sensors data characterised by moderate spatial resolution (e.g., Landsat) has shown its potential; particularly in higher energy coastal environments (e.g., Oceanic areas) where the magnitude of long-term erosion/accretion processes (e.g., decadal) can be resolved by the abovementioned sensors. However, the spatial resolution of these data may prevent an accurate analysis in microtidal coastal environments (e.g., Mediterranean Sea), especially for analyses focused on a short-term period (e.g., few years). This is mainly due to the high level of uncertainty associated with the occurrence of erosion/accretion processes of lower magnitude detected by EO sensors retaining a moderate spatial resolution. Within this context, this work was conceived to evaluate the potentialities of the Copernicus Very High Resolution (VHR) optical datasets (spatial resolution: 2-4 m) for assessing the shoreline evolution trends in an exemplifying urbanised coastal area of the Mediterranean Sea (i.e., Lido di Ostia, Rome, Italy), over a short-term period (i.e., 4 years). To achieve this objective, an automatic technique of shoreline detection and extraction at subpixel level was tested. Results allowed to: i) detect a shoreline evolution trend coherent with the geomorphological characteristics of the study area; ii) smoothly identify/quantify fine-scale variations of accretion/erosion patterns along the coast. This is extremely important to map the areas most exposed to shoreline erosion hazard/risk.
Evaluating the potentialities of Copernicus Very High Resolution (VHR) optical datasets for assessing the shoreline erosion hazard in microtidal environments / Cenci, Luca; Pampanoni, Valerio; Laneve, Giovanni; Santella, Carla; Boccia, Valentina. - 2:(2021), pp. 81-84. (Intervento presentato al convegno 10th AIT International Conference tenutosi a Virtual Event) [10.978.88944687/00].
Evaluating the potentialities of Copernicus Very High Resolution (VHR) optical datasets for assessing the shoreline erosion hazard in microtidal environments
Valerio Pampanoni;Giovanni Laneve;
2021
Abstract
In the past years, several studies have shown that Earth Observation (EO) data can be successfully used for analysing shoreline evolution trends and assessing coastal erosion hazard/risk. Within this framework, the exploitation of long-term archives of sensors data characterised by moderate spatial resolution (e.g., Landsat) has shown its potential; particularly in higher energy coastal environments (e.g., Oceanic areas) where the magnitude of long-term erosion/accretion processes (e.g., decadal) can be resolved by the abovementioned sensors. However, the spatial resolution of these data may prevent an accurate analysis in microtidal coastal environments (e.g., Mediterranean Sea), especially for analyses focused on a short-term period (e.g., few years). This is mainly due to the high level of uncertainty associated with the occurrence of erosion/accretion processes of lower magnitude detected by EO sensors retaining a moderate spatial resolution. Within this context, this work was conceived to evaluate the potentialities of the Copernicus Very High Resolution (VHR) optical datasets (spatial resolution: 2-4 m) for assessing the shoreline evolution trends in an exemplifying urbanised coastal area of the Mediterranean Sea (i.e., Lido di Ostia, Rome, Italy), over a short-term period (i.e., 4 years). To achieve this objective, an automatic technique of shoreline detection and extraction at subpixel level was tested. Results allowed to: i) detect a shoreline evolution trend coherent with the geomorphological characteristics of the study area; ii) smoothly identify/quantify fine-scale variations of accretion/erosion patterns along the coast. This is extremely important to map the areas most exposed to shoreline erosion hazard/risk.File | Dimensione | Formato | |
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