Spatial data acquisition is a critical process for the identification of the coastline and coastal zones for scientists involved in the study of coastal morphology. The availability of very high-resolution digital surface models (DSMs) and orthophoto maps is of increasing interest to all scientists, especially those monitoring small variations in the earth’s surface, such as coastline morphology. In this article, we present a methodology to acquire and process high resolution data for coastal zones acquired by a vertical take off and landing (VTOL) unmanned aerial vehicle (UAV) attached to a small commercial camera. The proposed methodology integrated computer vision algorithms for 3D representation with image processing techniques for analysis. The computer vision algorithms used the structure from motion (SfM) approach while the image processing techniques used the geographic object-based image analysis (GEOBIA) with fuzzy classification. The SfM pipeline was used to construct the DSMs and orthophotos with a measurement precision in the order of centimeters. Consequently, GEOBIA was used to create objects by grouping pixels that had the same spectral characteristics together and extracting statistical features from them. The objects produced were classified by fuzzy classification using the statistical features as input. The classification output classes included beach composition (sand, rubble, and rocks) and sub-surface classes (seagrass, sand, algae, and rocks). The methodology was applied to two case studies of coastal areas with different compositions: a sandy beach with a large face and a rubble beach with a small face. Both are threatened by beach erosion and have been degraded by the action of sea storms. Results show that the coastline, which is the low limit of the swash zone, was detected successfully by both the 3D representations and the image classifications. Furthermore, several traces representing previous sea states were successfully recognized in the case of the sandy beach, while the erosion and beach crests were detected in the case of the rubble beach. The achieved level of detail of the 3D representations revealed new beach characteristics, including erosion crests, berm zones, and sand dunes. In conclusion, the UAV SfM workflow provides information in a spatial resolution that permits the study of coastal changes with confidence and provides accurate 3D visualizations of the beach zones, even for areas with complex topography. The overall results show that the presented methodology is a robust tool for the classification, 3D visualization, and mapping of coastal morphology.

This paper presents a decision support model that assesses offshore suitability for floating wind turbine installation. The model is based on Multi-Criteria Analysis and Geographic Information Systems. An implementation of the model for the Aegean Sea is also presented. The methodological approach followed consists of four stages. The first stage excludes sites that are inappropriate for wind turbine siting based on legislative constraints. At the second stage, a set of evaluation criteria are used in order to identify the most suitable areas for floating wind turbine installation. Next stage is the economic evaluation of the highest-scored sites, as they resulted from final suitability map. Finally, a sensitivity analysis on the weights of the criteria is carried out. Results indicated that only a small percentage of the case study is characterised as appropriate for floating wind turbine siting, although wind potential is considered strong in more sites.

This contribution addresses the need for a simple model for managers to employ when planning strategies for the management of touristic beaches under sea level rise. A methodological framework was developed and tested in two Aegean archipelago islands (Lesvos and Rhodes, Greece). The scheme can represent the status of touristic island beaches, based on easily obtained variables/indicators and projections of beach erosion/retreat under different scenarios of mean sea level rise (MSLR) and extreme events. Information on beach geomorphological characteristics, environmental setting, water quality, management, and services (such as those used in the “Blue Flag” classification) was collated/collected and beach erosion/retreat due to CV & C was estimated through suitable ensembles of cross-shore (1-D) morphodynamic models. A Strength-Weaknesses-Opportunities-Threats (SWOT) framework was employed to assist in the selection of indicators and multicriteria analysis used to optimize indicator weights and rank beaches according to their sustainability under sea level rise. Implementation of the framework at the two islands has shown that: the majority of Lesvos and Rhodes beaches (82% of a total of 217 beaches and 58% of a total of 97 beaches, respectively) can be classified as beaches with no, or minimal, human interference, suggesting that under environmentally sound coastal management further touristic development might be afforded; there could be very significant effects of the sea level rise on the carrying and buffering capacities of the most developed (“Blue Flag”) beaches, with some expected even under conservative projections to be completely eroded by 2100, unless technical adaptation measures are taken; and using the proposed framework, touristic beaches can be rapidly ranked in terms of their resilience to sea level rise and their development potential, allowing prioritization of effective management responses.

The priority substances of List I, 76/464/EEC Directive, some of which belong to the new Water Framework Directive 2000/60/EC, have been monitored in the surface waters of Greece through the developed network of 53 sampling stations. The analytical methods used for the determination of these substances included Purge and Trap-Gas chromatography-Mass spectrometry for volatile and semivolatile organic compounds, Gas Chromatography-Electron Capture Detection for organochlorine insecticides, High Performance Liquid Chromatography for pentachlorophenol and Atomic Absorption Spectrometry for metals. The results have shown the presence of several priority substances in Greek surface waters, in most cases at concentrations well below the regulatory limits. However, non-compliance was observed for a limited number of compounds. The monitoring network and the analytical determinations have to be expanded to more water bodies and more priority substances, in order to safeguard the quality of Greek surface waters.