Anastasia Patera

The analysis of the 2002 Prestige tanker accident showed how public misinformation can worsen marine pollution incidents, rendering their management suboptimal as these evolve, thus raising the issue of appropriately informing and educating coastal and island populations who are at risk. Two decades later, developments in electronic platforms, including Geographic Information Systems (GIS), the Automatic Identification System (AIS) for ship signal transmission, and social media, provide a set of means for public monitoring of such incidents, creating the possibility to antagonise effectively erroneous or malevolent information, which can hinder efficient actions for containing marine pollution risks even without active training of the populations concerned. The authors, in the framework of the development of the Marine Coastal Observatory and Risk Management project “AEGIS+”, have developed E-S.A.V.E., an online innovative platform that (a) meets the needs of different users as revealed by a survey run across groups of them, (b) uses a suitable Geographic Information System (GIS) environment, (c) cooperates with public authorities, for the reliable update of automated systems, and (d) employs an artificial intelligence (AI)-supported tool for social media monitoring; the platform also provides educational resources and information on national and international resources on marine environmental protection and sustainable maritime logistics.

The analysis of the 2002 Prestige tanker accident showed how public misinformation can worsen marine pollution incidents, rendering their management suboptimal as these evolve, raising thus the issue of appropriately informing and educating coastal and island populations at risk. Two decades later, developments in electronic platforms, Geographic Information Systems (GIS), in Automatic Identification System (AIS) for ship signal transmission, and in social media, provide a set of means for public monitoring of such incidents, creating the possibility to antagonize effec-tively erroneous, or malevolent information which can hinder efficient actions for containing ma-rine pollution risks even without active training of populations concerned. The authors, in the framework of development of the Marine Coastal Observatory and Risk Management project “AEGIS+”, have developed E-S.A.V.E., an online platform which: a) meets the needs of different users as revealed by a survey run across groups of them, b) uses a suitable Geographic Infor-mation Systems (GIS) environment, c) cooperates with public authorities, for the reliable update of automated systems, and d) employs an artificial intelligence (AI) supported tool for social me-dia monitoring; the platform also provides educational and information national and interna-tional resources on marine environmental protection and sustainable maritime logistics.

Environmental Impact of Maritime Logistics Using Satellite Data

Nowadays, coastal areas are exposed to multiple hazards of increasing severity, such as coastal floods, erosion, subsidence due to a combination of natural and anthropogenic factors, including climate change and urbanisation. In order to cope with these challenges, new remote sensing monitoring solutions are required that are based on knowledge extraction and state of the art machine learning solutions that provide insights into the related physical mechanisms and allow the creation of innovative Decision Support Tools for managing authorities. In this paper, a novel user-friendly monitoring system is presented, based on state-of-the-art remote sensing and machine learning approaches. It uses processes for collecting and analysing data from various heterogeneous sources (satellite, in-situ, and other auxiliary data) for monitoring land cover and land use changes, coastline changes soil erosion, land deformations, and sea/ground water level. A rule-based Decision Support System (DSS) will be developed to evaluate changes over time and create alerts when needed. Finally, a WebGIS interface allows end-users to access and visualize information from the system. Experimental results deriving from various datasets are provided to assess the performance of the proposed system, which is implemented within the EPIPELAGIC bilateral Greece-China project. The system is currently being installed in the Greek case study area, namely Thermaikos Gulf in Thessaloniki, Greece.

Marine spatial planning (MSP) has been established as the appropriate policy framework to study and resolve conflicts that arise among various activities. A pre-requisite for the successful implementation of MSP is the availability of efficient tools to support decision-makers and enhance stakeholders’ engagement. In this paper, a webGIS application is proposed that is able to assess the intensity of conflicts among marine activities; the area of the Cyclades in the Aegean Sea was used as a case study. The webGIS application allows the visualization of existing activities, the delineation of conflicting activities, the detection of areas where multiple conflicts co-exist, and the delineation of areas of conflicts based on specific criteria. The webGIS application is available via a user-friendly interface as well as allowing interaction with users by providing them the opportunity to comment on the results and/or exchange ideas with other users of various groups; therefore, the participatory process, a creative stage in MSP, is further supported. The usefulness of such tools in coastal and marine planning and the decision-making process are further discussed.

Nowadays, the importance of coastal areas is greater than ever, with approximately 10% of the global population living in these areas. These zones are an intermediate space between sea and land and are exposed to a variety of natural (e.g. ground deformation, coastal erosion, flooding, tornados, sea level rise, etc.) and anthropogenic (e.g. excessive urbanisation) hazards. Therefore, their conservation and proper sustainable management is deemed crucial both for economic and environmental purposes. The main goal of the Greece-China bilateral research project “EPIPELAGIC: ExPert Integrated suPport systEm for coastaL mixed urbAn – industrial – critical infrastructure monitorinG usIng Combined technologies” is the design and deployment of an integrated Decision Support System (DSS) for hazard mitigation and resilience. The system exploits near-real time data from both satellite and in-situ sources to efficiently identify and produce alerts for important risks (e.g. coastal flooding, soil erosion, degradation, subsidence), as well as to monitor other important changes (e.g. urbanization, coastline). To this end, a robust methodology has been defined by fusing satellite data (Optical/multispectral, SAR, High Resolution imagery, DEMs etc.) and in situ real-time measurements (tide gauges, GPS/GNSS etc.). For the satellite data pre-processing chain, image composite/mosaic generation techniques will be implemented via Google Earth Engine (GEE) platform in order to access Sentinel 1, Sentinel 2, Landsat 5 and Landsat 8 imagery for the studied time period (1991-2021). These optical and SAR composites will be stored into the main database of the EPIPELAGIC server, after all necessary harmonization and correction techniques, along with other products that are not yet available in GEE (e.g. ERS or Sentinel-1 SLC products) and will have to be locally processed. A Machine Learning (ML) module, using data from this main database will be trained to extract additional high-level information (e.g. coastlines, surface water, urban areas, etc.). Both conventional (e.g. Otsu thresholding, Random Forest, Simple Non-Iterative Clustering (SNIC) algorithm, etc.) and deep learning approaches (e.g. U-NET convolutional networks) will be deployed to address problems such as surface water detection and land cover/use classification. Additionally, in-situ or auxiliary/cadastral datasets will be used as ground truth data. Finally, a Decision Support System (DSS), will be developed to periodically monitor the evolution of these measurements, detect significant changes that may indicate impending risks and hazards, and issue alarms along with suggestions for appropriate actions to mitigate the detected risks. Through the project, the extensive use of Explainable Artificial Intelligence (xAI) techniques will also be investigated in order to provide “explainable recommendations” that will significantly facilitate the users to choose the optimal mitigation approach. The proposed integrated monitoring solutions is currently under development and will be applied in two Areas of Interest, namely Thermaic Gulf in Thessaloniki, Greece, and the Yellow River Delta in China. They are expected to provide valuable knowledge, methodologies and modern techniques for exploring the relevant physical mechanisms and offer an innovative decision support tool. Additionally, all project related research activities will provide ongoing support to the local culture, society, economy and environment in both involved countries, Greece and China.

The assessment of seawater quality in coastal areas is an important issue as it is related to the welfare of coastal ecosystems, a prerequisite for the provision of the related ecosystem services. During the last decades, marine eutrophication has become an important problem in coastal waters as a result of nutrient inputs increase. Consequently, there is need for appropriate methods and tools to assess the eutrophication status of seawater which should be user-friendly to coastal managers and support the adoption of effective plans for the protection and sustainable development of the coastal environment. In this framework, a user-friendly webGIS application has been developed and the Strait of Mytilene at the southeastern part of the Island of Lesvos in the NE Aegean Sea, Greece, was used as a case study. The methodology includes, as a first step, the evaluation of the accuracy of spatial interpolators widely applied in oceanographic studies for assessing the spatial distribution of relevant variables. The most appropriate interpolator revealed for each variable is subsequently applied for the production of the representative thematic layer. The second step involves the integration of the information from the optimal thematic layers representing the spatial distributions of the variables under study; as a result, a new thematic layer illustrating the eutrophication status of the study area is produced. The webGIS application is fully available via a web browser and provides a number of geoprocessing modules developed in Python which implement the user interface, the application of the interpolation analytical tasks, the statistical evaluation toolset and the integration of the optimal interpolated layers. Suggestions for further improvement of the proposed webGIS application are discussed.

The development of methodologies for assessing water quality in coastal areas including mapping of eutrophication levels is a research area of high interest. A wide range of methodological approaches can be found in the literature, including multivariate techniques, since marine eutrophication is a multi-parametric phenomenon. In this context, statistical analysis and in particular Principal Component Analysis (PCA) have been widely applied. However, no attempt has been presented so far for mapping eutrophication levels based on information acquired from PCA results in integration with spatial analysis methods. The rapid development of Geographical Information Systems provides the appropriate framework for the development and application of methodologies integrating statistical analysis, spatial analysis methods and mapping techniques. This paper proposes such a methodological approach for assessing sea water quality in coastal areas. The methodology is clearly described and the Strait of Mytilene at the east of the Island of Lesvos in the NE Aegean Sea, Greece is used as a case study.