Erosion status of a sea cliff promontory bounding an ecologically important beach

Theodore, Panagou; Hasiotis, Thomas; Velegrakis, Adonis; Karambas, Theophanis V.; Emmanouel, Oikonomou; Dimitriadis, Charalampos

doi:10.1007/s11852-020-00756-6

Cited by 6 publications

(4 citation statements)

References 68 publications

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“…To reduce the impact of natural hazards on urbanized areas, as for example coastal erosion (Hurst et al, 2016;Panagou et al, 2020), cliffs, and landslides (Guida & Valente, 2019), resident people need to identify, assess and control various factors (Adam et al, 2016) that contribute to harm the affected area. As it has been described, these factors depend on a large set of information, which is often owned by different authorities, and which ranges from sensor data, demographic data, land use data, transportations, etc.…”

Section: Living Labs To Test Resultsmentioning

confidence: 99%

Development of Smart Applications for Coastal Erosion and Landslide Risk Reduction

Castelli

Greco

2020

HSSR

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Purpose: Cloud computing has opened new opportunities in disastrous natural early warning. The scientific community has recognized the significance of the geo-analytic approach in complex decision-making processes for critical situations due to natural events such as coastal erosion and landslides. The paper describes the progress in the development of ITC dissemination systems for the population to promote the preparedness toward the coastal risk. Methodology: To achieve these goals an information system based on an Open Source Cloud Computing platform following a PaaS (Platform as a Service) and SaaS (Software as a Service) approaches has been used. Main Findings: The southern coast of Sicily (Italy) and the islands of the archipelagos of Malta are highly exposed to risks coming from the sea. Such coasts are subjected to fast erosion due to natural and anthropic causes which involve the failure of cliffs, the triggering of localized erosions, and the possibility of flooding. Implications/Applications: The research effort aims to build an interconnected framework through the implementation of smart technology, which involves surveillance, early warning, and reduction of coastal threats, with a specific goal to educate citizens regarding flood hazards, coastal waters, and degradation, cliff collapses and safety steps. Novelty/Originality of this study: The study expresses a different perspective on cloud computing to prevent the effects of disastrous natural events and to provide indications of areas susceptible to risk.

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Section: Living Labs To Test Resultsmentioning

confidence: 99%

Development of Smart Applications for Coastal Erosion and Landslide Risk Reduction

Castelli

Greco

2020

HSSR

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“…Methods of data capture have evolved from ground-based physical field survey using levels and theodolites (Smith and Zarillo, 1990), to comparison of satellite imagery or cartographic charts (Bray and Hooke, 1997), terrestrial photogrammetry (Gulyaev and Buckeridge, 2004), terrestrial and aerial laser scanning (Dewez Thomas et al, 2013, Young et al, 2014, with Unoccupied Aerial Vehicles (UAVs) surveys now becoming a more common approach (Esposito et al, 2017). Of these methods, the LiDAR-based aerial and terrestrial laser scanning have dominated cliff erosion studies in the past decade (Letortu et al, 2018, Theodore et al, 2020, Young et al, 2009, Bezore et al, 2019, Katz and Mushkin, 2013, owing to their ability to produce 3D point clouds (hereafter denoted as "point clouds") that allow visualisation and analysis of landscapes in three dimensions. More recently, UAVs with the ability to collect Structure from Motion (SfM) photogrammetry have provided a cost-effective way to collect data with high spatial resolution and capability to produce point clouds (Mancini et al, 2017, Dewez Thomas et al, 2013, thereby allowing for the generation of extensive multi-temporal datasets (Ierodiaconou et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Using UAV-Derived Point Clouds to measure high resolution cliff dynamics in soft lithologies: Demons Bluff, Victoria, Australia

Doran,

Kennedy,

McCarroll

et al. 2024

Preprint

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Abstract. Unoccupied aerial vehicles (UAVs) have revolutionised data collection on the Earth’s surface. Through aerial photogrammetry, very high-resolution digital surface models can be produced enabling contemporary research on landscape stability. There are however significant limitations in the imaging of vertical and overhanging landforms when using aerial platforms for data collection. Rather than reconstructing change from a digital surface model, direct analysis of generated point clouds is likely the key for understanding landform change in these morphologically complex environments. In this study, UAV’s were used to collect aerial imagery generating a high spatio-temporal resolution timeseries comprising of thirty point cloud datasets spanning four years for the steeply sloped Demons Bluff cliff located on the Great Ocean Road, Victoria, Australia. A method was developed to analyse the large quantity of 3D point cloud datasets. It was then possible to capture changes in cliff face morphology, enabling us to enhance our understanding of the erosional processes in coastal cliff environments. Over the study, the retreat rate for the upper half of the cliff face was 0.67 m/year (0.60 m3/m/yr). Cliff erosion was found to be dominated by 9 high magnitude, cliff-top collapses that exceeded 1,000 m3 (up to 9,500 m3) and terminated mid-way down the cliff. Below this point, several slab detachments were observed. Pre-collapse deformation was detected before collapses > 300 m3 with success (75 % of the time) in areas with a complete timeseries over the four-year period. Deformation was observed to occur in two ways, and both were observed to be eventuate in high magnitude (> 1,000 m3) collapse. The first which occurred prior to most high magnitude collapses (> 500 m3) was caused by the expansion of tension cracks behind the cliff-top, and the second which was characterised by smaller collapse volumes (> 100–500 m3) was initiated by rock slabs fracturing and cleaving away from the cliff face and was proceeded by high magnitude failure (< 1000 m3). An additional 14 instances of lean have been identified that are yet to result in collapse and should continue to be monitored to assess the success of this method with the forecasting of future collapse locations. Ultimately, this provides the ability to identify potential locations for future collapses which could aid in the development of an early warning system for cliff collapse to improve the management of volatile cliff environments that pose threats to infrastructure and public safety.

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“…This process is of particular importance since sandy beaches represent, at the same time, important habitats 2 , protective barriers from sea flooding of neighboring ecosystems and infrastructures 3 , as well as an economically fundamental natural resource 4 . Pocket beaches are usually bounded by sea cliff promontories, which are exposed to environmental forces driven by both marine and subaerial processes 5 forming gullies, unstable cliff overhangs and detachment surfaces 6 , imposing risks both at the fronting beaches but also to infrastructures at the top of the cliffs. Sea cliff promontories and embayed sandy beaches form the main habitats, especially in island settings.…”

Section: Introductionmentioning

confidence: 99%

A holistic high-resolution monitoring approach in studying coastal erosion of a highly touristic beach, Coral Bay, Cyprus

Hasiotis,

Andreadis,

Chatzipavlis

et al. 2023

Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023)

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In the frame of "BEACHTECH" project, Coral Bay, one of the most touristic beaches in Pegeia (west Cyprus) occasionally experiencing intense coastal erosional issues, was selected to be studied as a pilot site using several surveying techniques for coastal monitoring/evaluation. Coral Bay is a typical pocket beach with minimal sediment supply, affected mainly by west to south wind/wave forcing and swell waves. A dense grid of topo-bathymetric, geomorphological, laser scanner and repeated drone topographical data was collected and analysed. A coastal observatory comprising of a weather station, a fully automated video system and a wave buoy was permanently installed to monitor and correlate shoreline variability and wind/wave forcing in a high spatio-temporal resolution. Moreover, a high-frequency hydrodynamic experiment was carried out to investigate the nearshore current regime. Observations during a 2.5-month period show cross -and along -shore variations under a low intensity forcing with contrasting patterns of beach loss or gain. The results verify the energetic hydrodynamic regime of the Coral-Bay coastal zone even during mild hydrodynamic conditions and it is envisaged to contribute to proposing rational management plans and technical measures in order to reduce the beach erosional risk.

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Erosion status of a sea cliff promontory bounding an ecologically important beach

Cited by 6 publications

References 68 publications

Development of Smart Applications for Coastal Erosion and Landslide Risk Reduction

Development of Smart Applications for Coastal Erosion and Landslide Risk Reduction

Using UAV-Derived Point Clouds to measure high resolution cliff dynamics in soft lithologies: Demons Bluff, Victoria, Australia

A holistic high-resolution monitoring approach in studying coastal erosion of a highly touristic beach, Coral Bay, Cyprus

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