Coastal areas are dynamic multidimensional systems challenged by the complex interactions between natural, environmental, and human-induced pressures, as well as the ever-changing climate. A comprehensive evaluation of their spatial and temporal features enables the development of effective practices required to apply integrated coastal zone management (ICZM) policies. ICZM seeks to address the vulnerability of coastal areas in an attempt to mitigate their weaknesses and increase their resilience. Hence, coastal vulnerability assessment is a prerequisite to proceed with optimal adaptation or upgrading actions. Currently, assessments are performed by considering different approaches related to dividing coastal areas into segments to observe the spatial variations of vulnerability. The present research seeks to investigate the impact of the spatial segmentation of coastal areas on the assessment of their vulnerability. To achieve this, a case study of the coastal zone of the Municipality of Thebes, located in the Northeastern Corinthian Gulf, Greece, is examined. Five segmentation approaches are applied in terms of a physical-based vulnerability assessment for two different time horizons, (a) the present and (b) the future, by incorporating the climate change impacts. This study allows for optimizing practices to estimate vulnerability parameters and obtain reliable results for practical applications while reducing time-consuming analyses.

Port infrastructure plays an important role in the economic and social activities of the regions they serve. Pressures induced by the corrosive marine environment and weather conditions, unexpected events associated with climate change, the usually high freight and vehicle loading conditions, the dynamic load of the equipment, and insufficient maintenance and rehabilitation measures that sometimes are not enough to repair an in-service facility, increase the susceptibility of port structures to rapid aging and deterioration. To ensure port infrastructure safety and reliability, and to maintain operational efficiency, port managers are tasked with forming successful inspection schemes for structural condition monitoring. Within this context, identifying the capabilities and prioritizing existing inspection techniques allow for optimizing resources (cost, time, personnel). The issue of performance assessment for commonly used Non-Destructive Testing techniques has received significant research interest. However, state-of-the-art Unmanned Aerial Vehicle techniques have not been previously involved in studies that assess the performance of various inspection techniques. Hence, the present research seeks to introduce Unmanned Aerial Vehicles techniques into multi-criteria performance assessment practices of inspection techniques for port concrete infrastructure. Three Non-Destructive Techniques: a) Infrared Thermography, b) Ground Penetrating Radar, and c) Impact-Echo, are compared to camera-based Unmanned Aerial Vehicle techniques linked to Close Range Photogrammetry applications. A qualitative approach, including a literature review and expert judgment, is applied to acquire data required for Multi-Criteria Decision Analysis practices with the Preference Ranking Organization METHod for Enrichment Evaluation methodology. The ranking output of the applied model is validated with other multi-criteria methods to ensure the robustness of the results. The obtained results for the specific set of criteria will assist decision-makers in selecting the most suitable technique for inspecting surface or sub-surface defects in port concrete infrastructure. Highlights The integration of UAV-driven techniques into current practices for assessing the performance of inspection techniques affects the ranking order The prioritization of the inspection techniques is conducted qualitatively (expert judgment and literature survey) by implementing the PROMETHEE method A camera-based UAV technique improves the practical part of inspections and provides flexibility A camera-based UAV technique is the optimal inspection technique for detecting surface defects, while Impact Echo is preferred for sub-surface defects

Ports play a significant role in the economic and social activities of the areas they serve. However, the adverse effects of the harsh and highly corrosive environments that ports operate in, along with phenomena related to the climate crisis and insufficient maintenance practices, increase port infrastructure's susceptibility to rapid degradation. This degradation can be aesthetic, functional, or structural and often leads to loss of serviceability at either a component (local and national) level or a global level. Moreover, many port structures have reached the limit of their lifetime, thus introducing the concept of extending their lifespan as a financially attractive alternative to constructing new facilities. Therefore, port operators pursue monitoring the structural integrity of the structures through an inspection plan aiming to reduce their maintenance and rehabilitation costs and ensure the safety of both the port infrastructure itself and human lives. Optimising monitoring approaches to enable damage detection and condition assessment can be achieved through the employment of Non-Destructive Testing (NDT) and Remote Sensing (RS) techniques. The current surge of using Unmanned Aerial Vehicles (UAVs) for both RS and NDT monitoring practices has proved promising since UAVs provide improved accessibility, increased inspection speed, and reduced safety hazards. The present paper is focused on investigating and evaluating the recent advances in UAV-driven port infrastructure monitoring. For this purpose, a comprehensive review of UAVs applications combined with NDT Infrared Thermography (IRT) and Ground Penetrating Radar (GPR) or RS Close Range Photogrammetry (CRP) and Light Detection and Ranging (LiDAR) is carried out to assess the potential and the limitations of the UAV-based monitoring approaches. This research provides valuable information on enhancing management strategies by upgrading port monitoring practices.

Port vulnerability assessment is inherently linked to the delivery of sustainable and resilient infrastructure. Identifying the vulnerabilities and weaknesses of a port system allows for the minimization of disaster effects and optimization of maintenance, repair, or mitigation actions. The current port vulnerability assessment practices are built upon the examination of a diversity of indicators (parameters), including technical, physical, environmental, and socioeconomic pressures. From an engineering perspective, and given that ports are tangible infrastructure assets, their vulnerability is highly affected by the structural condition of their facilities. Hence, the present research seeks to enhance port vulnerability assessment by introducing structural condition parameters based on Structural Health Monitoring applications. The four fishing and leisure harbors of the Municipality of Thebes, located in central Greece, were used as a case study. Two approaches were considered for the harbors’ vulnerability assessments: (a) enabling and (b) disabling the use of the proposed parameters. In situ inspections were conducted with the employment of an Unmanned Aerial Vehicle (UAV) for condition monitoring. UAV data were analyzed to generate geospatial images that allow for the mapping and detecting of defects and failures in port infrastructure. The overall research assists decision-makers in gaining valuable insight into the system’s vulnerabilities and prioritizing their interventions.

Ports act as hubs for international trade and transport, strengthening the economies of the regions they serve. To maintain their undisrupted operations, efficient port management systems rely on Structural Health Monitoring practices to detect defects and assess infrastructure performance. Regarding port concrete pavements, condition assessment includes crack detection. Currently, advanced algorithms and methodologies for image processing or machine learning applications are used for surface crack detection with images captured during in-situ inspections. The growing urge to employ unmanned aerial vehicles (UAVs) equipped with high-resolution cameras is driving further research into image processing methods. This study provides an insightful approach for real-time crack detection in port concrete pavements that takes advantage of the geospatial information included in UAV imagery. The proposed methodology is based on the synergetic application of programming and Geographic Information System tools. Widely used crack detection methods and algorithms are herein enhanced with geospatial analysis modules that help to manage photogrammetry metadata generated by processing UAV data. Geographic Information System tools are employed to add a new perspective to crack detection by supporting the visualization and interpretation of geospatial processed images to locate cracks and examine crack propagation. The investigation includes a periodic field test conducted at Lavrio Port, a Greek port located at the southeastern tip of Attica. Overall, the combined methodology returns results with high accuracy (approximately 95%), thus having a practical application in the engineering community that shifts to scalable solutions for mapping cracks in large port concrete surfaces remotely inspected with UAVs.