A ‘fit-for-purpose’ approach is developed, tested and presented for cadastral surveys through increased owners’ participation using new technology and m-government services. Three case studies are reported, for urban, suburban and rural areas, with a combined use of two mobile applications: a commercial software package (ESRI’s Collector for ArcGIS) and an opensource self-developed application named BoundGeometry. The parameters of time, quality and accuracy are assessed and the identified difficulties are classified. It is concluded that the method is applicable both in developed and developing countries, and each time adjustable to the available infrastructure.

Post-disaster flood risk assessment is extremely difficult owing to the great uncertainties involved in all parts of the assessment exercise, e.g., the uncertainty of hydrologic–hydraulic models and depth–damage curves. In the present study, a robust and fast data-driven tool for residential flood risk assessment is introduced. The proposed tool can be used by scientists, practitioners and/or stakeholders as a first step for better understanding and quantifying flood risk in monetary terms. Another contribution of the present study is the fitting of an equation through depth–damage points provided by the Joint Research Center (JRC). The approach is based on hydrologic simulations for different return periods, employing a free and widely used software, HEC-HMS. Moreover, flood depths for the study area are estimated based on hydrodynamic simulations employing the HEC-RAS software and the Inverse Distance Weighting (IDW) interpolation method. Finally, flood risk, in monetary terms, is determined based on the flood depths derived by the coupling of hydrodynamic simulations and the IDW method, depth–damage curves reported in the literature, vulnerability of residential areas and the residential exposure derived by employing GIS tools. The proposed tool is applied in a highly urbanized and flood-prone area, Mandra city, in the Attica region of Greece. The results are maps of flood depths and flood risk maps for specific return periods. Overall, the results derived from the application of the proposed approach reveal that the tool can be highly effective for post-disaster flood risk management. However, it must be noted that additional information and post-disaster data are needed for the verification of the damages from floods. Additional information can result in better calibration, validation and overall performance of the proposed flood risk assessment tool.

Currently, there is a growing consensus that the use of more sustainable urban freight transportation has the potential to offer major energy and efficiency benefits which can be achieved through the appropriate combination of cargo bikes and the integration of drones into the urban logistics system. This study presents the results of a stepwise regression analysis that examines the role, benefits, and impact of electric vehicles such as e-bikes, cargo bikes, and drones for intermodal freight transportation in five Greek cities to support the green logistics paradigm. The results show that between routes of almost equal length, the most bicycle-friendly routes, such as routes along pedestrian areas or residential streets, should be avoided, as they reduce delivery speed and increase delivery costs in terms of energy and time expenditure. In addition, priority roads, which usually have higher traffic speeds and more trucks, are preferred by cyclists due to the quality of the road surface, even though the feeling of safety is lower on such roads. Finally, regarding drones, energy consumption is relatively low in the 0–5 mph and 6–10 mph wind speed ranges, indicating efficient energy use. In the 11–15 mph and 16–20 mph wind speed ranges, energy efficiency is significantly lower than the battery capacity, indicating that the cargo drone exhibits excessive energy consumption under these conditions.

While some countries have over centuries developed a nation-wide spatial framework, some others have been left behind. However, because of the global economic and social challenges, there is an urgent need for those countries to develop similar systems in a fast and efficient way for their economic survival. Building such a framework should be always based on each country's resources and capacities. In systematic cadastral registrations, the participation of owners has always been crucial for the success of the project. Within this concept, the authors investigate the potential of new tools to increase the participation of land right holders and local volunteers (non-professionals) and to enhance the cadastral surveying procedure. A hybrid “crowdsourcing” approach is proposed, mainly based on the direct participation of property rights holders in which the role of the cadastral surveyor is crucial. A commercial application for smartphones is tested. The smartphone's GPS is used only for the general positioning on the basemap to avoid gross errors when owners are not accustomed in using aerial photos. A recent orthoimage of 20 cm pixel size in urban areas and an orthoimage basemap of 50 cm pixel size in rural areas is used as the basemap. Once roughly positioned, owners may then digitise the boundary coordinates on the basemap off-line, with little training support; they may also work from a distance. In areas where the property boundaries are easily recognised on the basemap, boundary coordinates have the expected geometric accuracy that can be achieved on the basemap while no gross errors are detected. Attachment of photos is also possible (e.g. photos of the property or of the deeds). Restricted access to personal data may also be achieved. The method is also useful for cadastre updating purposes (e.g. the periodic updating of buildings database).

This paper is part of an ongoing research study on developing a methodology for the low-cost creation of the Digital Twin of an urban neighborhood for sustainable, transparent, and participatory urban management to enable low-and middle-income economies to meet the UN Sustainable Development Agenda 2030 successfully and timely, in particular SDGs 1, 7, 9, 10, 11, and 12. The methodology includes: (1) the creation of a geospatial data infrastructure by merging Building Information Models (BIMs) and 3D cadastral data that may support a number of applications (i.e., visualization of 3D volumetric legal entities), and (2) the use of Artificial Intelligence (AI) platforms, Machine Learning (ML), and sensors that are interconnected with devices located in the various property units to test and predict future scenarios and support energy efficiency applications. Two modular platforms are created: (1) to interact with the AI sensors for building tracking and management purposes (i.e., alarms, security cameras, control panels, etc.) and (2) to analyze the energy consumption data such as future predictions, anomaly detection, and scenario making. A case study is made for an urban neighborhood in Athens. It includes a dynamic weather simulation and visualization of different seasons and times of day in combination with internal energy consumption.

The treatment of osseous defects around teeth is a fundamental concern within the field of periodontology. Over the years, the method of grafting has been employed to treat bone defects, underscoring the necessity for custom-designed scaffolds that precisely match the anatomical intricacies of the bone cavity to be filled, preventing the formation of gaps that could allow the regeneration of soft tissues. In order to create such a patient-specific scaffold (bone graft), it is imperative to have a highly detailed 3D representation of the bone defect, so that the resulting scaffold aligns with the ideal anatomical characteristics of the bone defect. In this context, this article implements a workflow for designing 3D models out of patient-specific tissue defects, fabricated as scaffolds with 3D-printing technology and bioabsorbable materials, for the personalized treatment of periodontitis. The workflow is based on 3D modeling of the hard tissues around the periodontal defect (alveolar bone and teeth), scanned from patients with periodontitis. Specifically, cone beam computed tomography (CBCT) data were acquired from patients and were used for the reconstruction of the 3D model of the periodontal defect. The final step encompasses the 3D printing of these scaffolds, employing Fused Deposition Modeling (FDM) technology and 3D-bioprinting, with the aim of verifying the design accuracy of the developed methodοlogy. Unlike most existing 3D-printed scaffolds reported in the literature, which are either pre-designed or have a standard structure, this method leads to the creation of highly detailed patient-specific grafts. Greater accuracy and resolution in the macroarchitecture of the scaffolds were achieved during FDM printing compared to bioprinting, with the standard FDM printing profile identified as more suitable in terms of both time and precision. It is easy to follow and has been successfully employed to create 3D models of periodontal defects and 3D-printed scaffolds for three cases of patients, proving its applicability and efficiency in designing and fabricating personalized 3D-printed bone grafts using CBCT data.