New Coastal Video-Monitoring System Achievement and Development

Valentini, Nico; Damiani, Leonardo; Molfetta, Matteo Gianluca; Saponieri, Alessandra

doi:10.9753/icce.v35.management.11

Cited by 12 publications

(8 citation statements)

References 26 publications

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“…In order to obtain accuracy and precision metrics, optical images acquired by a video monitoring system installed in 2015 at Torre Canne, Italy (Apulia, South Italy) [28,36,60] are used to compare satellite versus in situ monitoring strategies. Video-derived images spatial resolution varies from decimeters to around 13 m, based on the distance of the near-alongshore footprint from the camera (Figure 3).…”

Section: Validation Datamentioning

confidence: 99%

Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region

Spinosa

Ziemba

Saponieri

et al. 2021

JMSE

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Remote sensing and satellite imagery have become commonplace in efforts to monitor and model various biological and physical characteristics of the Earth. The land/water interface is a continually evolving landscape of high scientific and societal interest, making the mapping and monitoring thereof particularly important. This paper aims at describing a new automated method of shoreline position detection through the utilization of Synthetic Aperture Radar (SAR) images derived from European Space Agency satellites, specifically the operational SENTINEL Series. The resultant delineated shorelines are validated against those derived from video monitoring systems and in situ monitoring; a mean distance of 1 and a maximum of 3.5 pixels is found.

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Section: Validation Datamentioning

confidence: 99%

Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region

Spinosa

Ziemba

Saponieri

et al. 2021

JMSE

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“…Passive and active remote sensing techniques are an essential element in the early identification of critical areas [40,49,53,54], since extensive in situ campaigns are too cost-and time-expensive in wide areas. Aerial images taken in 1992, 2005 and 2017 are used for the aim.…”

Section: Indicatorsmentioning

confidence: 99%

The DPSIR Approach for Coastal Risk Assessment under Climate Change at Regional Scale: The Case of Apulian Coast (Italy)

Bruno

Saponieri

Molfetta

et al. 2020

JMSE

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In the present paper, the coastal risk is assessed, at a regional scale, to produce a risk map that will help to prioritize policies and economic resources in coastal management and planning activities. The DPSIR method is here used taking into account processes and cause/effect relationship between Drivers and Pressures, which induce an alteration of actual State and, hence, Impacts on the environment, society and economy. The study area is located in South Italy (Apulia region), where the Risk Index is calculated and mapped for all municipalities facing the Adriatic and Ionian Seas. Both coastal Vulnerability and Exposure Indexes are firstly calculated according to the procedure suggested in the EUrosion project (EU model) as the product of specific indicators describing the state of coastal zones, their natural characteristics and both natural and anthropic pressures. Based on both EU model results and knowledge of states and pressures of the study area, a new modified model is then proposed (Mod.E.M.) and final risk maps compared. The comparison shows that new Vulnerability and Exposure indexes better describe the ongoing coastal processes and pressures and allow us to identify hot-spot sites where more detailed analyses could be further focused on. The Mod.E.M. has more than just a local significance since the case study includes coastal areas with so different characteristics, that it can be easily applied to other coastal regions. Moreover, to take into account climate change effects, Risk Index is evaluated under Representative Concentration Pathways R C P 4.5 and R C P 8.5 , mainly affecting the sea level rise and the storm surge level.

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“…The SWASH model was already used in previous studies (e.g., [27][28][29][30][31][32]). The model reliability in detecting the interaction between rubble mound breakwater with submerged berms and the incident random waves was validated by Celli et al [8].…”

Section: Models Validationmentioning

confidence: 99%

Random Wave-Induced Momentary Liquefaction around Rubble Mound Breakwaters with Submerged Berms

Celli

Ong

et al. 2020

JMSE

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The effects of submerged berms in attenuating the momentary liquefaction beneath rubble mound breakwaters under regular waves were investigated in a recent study. The present work aims to investigate the momentary liquefaction probabilities around and beneath breakwaters with submerged berms under random waves. The interaction between waves and breakwaters with submerged berms has been simulated through a phase-resolving numerical model. The soil response to the seabed pressure induced by random waves has been investigated using a poro-elastic soil solver. For three different breakwater configurations, the liquefaction depths under random wave conditions have been compared with those cases under representative regular waves. In the present study, the offshore spectral wave height ( H m 0 ) and the peak period ( T p ) of irregular waves are used as representative regular wave parameters. Results reveal the importance of considering random waves for a safe estimation of the momentary liquefaction probability. Indication about the minimum number of random waves, which is required to properly catch the liquefaction occurrences, has been also addressed.

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New Coastal Video-Monitoring System Achievement and Development

Cited by 12 publications

References 26 publications

Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region

Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region

The DPSIR Approach for Coastal Risk Assessment under Climate Change at Regional Scale: The Case of Apulian Coast (Italy)

Random Wave-Induced Momentary Liquefaction around Rubble Mound Breakwaters with Submerged Berms

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