http://repositorio.lnec.pt:8080/jspui/handle/123456789/52 Sat, 04 Apr 2026 21:09:13 GMT 2026-04-04T21:09:13Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1017131 Digital coast: a scientific proposal for it- based research in coastal regions for the next decade Oliveira, A. This document corresponds to the Research Program and associated Post-Graduation Program elaborated by the author in the scope of the process of certification for the functions of coordination of scientific research, according to Decree-Law no. 124/99, of April 20th. This Research Program identifies several research themes for the next decade related to the application of information technologies in coastal science and innovation of research. The selection of these themes is framed in the scientific national and international context, focused in particular in the activity of LNEC in this area through the research of the Information Technology in Water and Environment research group, led by the applicant, in collaboration with other divisions of the Hydraulics and Environment Department. After a brief overview of the theme and presentation of the rationale for the development of this work, the national and global context for the Program is presented, wrapping up with the presentation of the research strategy for the Information Technology in Water and Environment research group. From this strategy, the two research areas of this Habilitation Program are identified and briefly described. The first area is the creation and development of reliable, cross-scale, multi-process, on-demand coastal forecast framework for oceans to hydrographic basin application, from hydrodynamics to biogeochemistry. The second area is the creation and development of intelligent, high-resolution, user centered and inclusive coastal digital twins. The two following chapters present the state-of-the-art in these two areas, the challenges to be overcome and the general roadmaps for the tools to be developed in the next decade to address the societal challenges in the coastal regions. The two Research Studies are presented next, organized along 19 projects. For each project, the applicant presents the rationale behind it, along with its goals, describes the methodologies for its implementation and the results to be generated. The resources necessary for its implementation along with the expected partnerships and adequate funding sources are also described. Finally, the Post-Graduation Program is presented, providing multiple M.Sc. and Ph.D. education opportunities framed in the previous Research Program. A total of 9 Ph.D. and 6 M.Sc. proposals are presented. Thu, 01 Sep 2022 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1017131 2022-09-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1016705 Automatic identification of the wave runup line from camera images Martins, R.; Azevedo, A.; Jesus, G.; Oliveira, A.; Fortunato, A. B.; Oliveira , F.; Nahon, A.; Freire, P. We propose a novel methodology for an automated coastline runup detection from high-resolution remote camera images. As part of a multi-source integrated flood risk assessment platform, this methodology will further improve the characterization of the beach hydrodynamics and define automated procedures for the surveillance of coastal overtopping and overwash. Wed, 01 Jun 2022 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1016705 2022-06-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1016000 Model-driven engineering techniques and tools for machine learning-enabled IoT applications: a scoping review Korani, Z.; Moin, A.; Silva, A.; Ferreira, J. This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services. Sun, 01 Jan 2023 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1016000 2023-01-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1015612 Enhancing a coastal territorial vulnerability index: anticipating the impacts of coastal flooding with a local scale approach Barros, J.; Tavares, A.; Santos, P.; Freire, P. The coastal zone of mainland Portugal is characterized by its morpho-sedimentary diversity such as estuaries, lagoons, barrier islands, beaches, dunes and cliffs. The high population density and the multiplicity of land use, occupation and activities, makes it an area of great national strategic value. This transforms the coastal zone into a multi-hazard zone, where the occurrences related to coastal flooding and overtopping stand out. In the present work, a multidi mensional methodology called Coastal Territorial Vulnerability Index (CTVI) was developed and applied in three selected areas with a historical record of coastal impacts, to analyze, evaluate and interpret the local vulnerability. The methodology considers four components of coastal territorial vulnerability: morphology, land value, buildings and public areas characteristics. These four components are combined to calculate the CTVI. The results highlight the differences for the analyzed areas, allowing the differentiation of natural and artificial areas. In the natural areas a moderate CTVI predominates, while in the latter, a high and very high CTVI stands out. The results contribute to the development of a comprehensive coastal flood risk assessment and forecasting the impacts Mon, 01 Aug 2022 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1015612 2022-08-01T00:00:00Z