As the basis for analysis and management of heritage assets, 3D laser scanning and photogrammetric 3D reconstruction have been probed as adequate techniques for point cloud data acquisition. The European Directive 2014/24/EU imposes BIM Level 2 for government centrally procured projects as a collaborative process of producing federated discipline-specific models. Although BIM software resources are intensified and increasingly growing, distinct specifications for heritage (H-BIM) are essential to driving particular processes and tools to efficiency shifting from point clouds to meaningful information ready to be exchanged using non-proprietary formats, such as Industry Foundation Classes (IFC). This paper details a procedure for processing enriched 3D point clouds into the REVIT software package due to its worldwide popularity and how closely it integrates with the BIM concept. The procedure will be additionally supported by a tailored plug-in to make high-quality 3D digital survey datasets usable together with 2D imaging, enhancing the capability to depict contextualized important graphical data to properly planning conservation actions. As a practical example, a 2D/3D enhanced combination is worked to accurately include into a BIM project, the length, orientation, and width of a big crack on the walls of the Castle of Torrelobatón (Spain) as a representative heritage building.
Rural areas in Europe represent outstanding examples of Cultural and Natural Heritage (CNH) that could be used as a valuable asset for social and economic development. This paper describes the process for developing a monitoring platform based on Key Performance Indicators (KPI) and implemented in six rural areas around Europe. The goal of this monitoring system is to provide evidence of the role of CNH in rural areas as a driver for sustainable growth. Several data collection procedures are described, including regular, non-regular and co-monitoring. In order to combine the selected cross-thematic and multi-scale KPIs, weights have been assigned to indicators, according to the knowledge provided by domain experts and using group decision making (GDM) techniques. A detailed description of the dashboards developed for the monitoring platform and all the information gathered is included. Several dashboards have been designed focusing on KPI values and their evolution.
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