The monitoring and metric assessment of piles of natural or man-made materials plays a fundamental role in the production and management processes of multiple activities. Over time, the monitoring techniques have undergone an evolution linked to the progress of measure and data processing techniques; starting from classic topography to global navigation satellite system (GNSS) technologies up to the current survey systems like laser scanner and close-range photogrammetry. Last-generation 3D data management software allow for the processing of increasingly truer high-resolution 3D models. This study shows the results of a test for the monitoring and computing of stockpile volumes of material coming from the differentiated waste collection inserted in the recycling chain, performed by means of an unmanned aerial vehicle (UAV) photogrammetric survey and the generation of 3D models starting from point clouds. The test was carried out with two UAV flight sessions, with vertical and oblique camera configurations, and using a terrestrial laser scanner for measuring the ground control points and as ground truth for testing the two survey configurations. The computations of the volumes were carried out using two software and comparisons were made both with reference to the different survey configurations and to the computation software.

The research on Carlo III bridge in Moiano (Benevento, Italy) has been an opportunity for testing the HBIM methodology to the architectural heritage in terms of not only gathering information but as a design tool. The bridge, almost without previous drawings and documents, was surveyed with an integrated approach using laser scanner, photogrammetry and topography. Data produced a metrically reliable HBIM model, complete with graphical and non-graphical information, to be used in a maintenance and restoration project.

Cultural heritage digitization and 3D modelling processes are mainly based on laser scanning and digital photogrammetry techniques to produce complete, detailed and photorealistic three-dimensional surveys: geometric as well as chromatic aspects, in turn testimony of materials, work techniques, state of preservation, etc., are documented using digitization processes. The paper explores the topic of 3D documentation for conservation purposes; it analyses how geomatics contributes in different steps of a restoration process and it presents an overview of different uses of 3D models for the conservation and enhancement of the cultural heritage. The paper reports on the project to digitize the earthenware frieze of the Ospedale del Ceppo in Pistoia (Italy) for 3D documentation, restoration work support, and digital and physical reconstruction and integration purposes. The intent to design an exhibition area suggests new ways to take advantage of 3D data originally acquired for documentation and scientific purposes.

Current close-range photogrammetry makes it possible to obtain 3-D models from imagery acquired with off-the-shelf digital cameras or other low-cost devices and processed with affordable software or apps in an almost automatic way. For this reason, a wider and wider public (often without a specific training, as archaeologists, architects, landscape planners, digital artists) is using these tools and their outcomes in many fields. However, the drawback of its ease of use is that photogrammetry is often used without any critical awareness of the metric quality of the results. Therefore, it is necessary to bridge the growing gap between the spread of photogrammetric techniques and their use through appropriate educational processes. The paper presents and explain the results of the project “Education and training resources on digital photogrammetry”, financed in 2018 by ISPRS as part of the “Educational and Capacity Building Initiative” programme. The project, after evaluating the current teaching methodologies and techniques, is producing and sharing original teaching materials (like videos and datasets) on digital photogrammetry. The aim is to transform the traditional transmissive didactic model in a newer one in which the students have an active role and improve their proficiencies solving actual case studies in practice. This induces students to rethink and better understand all the steps of the photogrammetric project design, acquisition and processing but above all to acquire greater skills to critically evaluate the acquired data and results.

Keywords: Workflow, Photogrammetry, Laser Scanning, Integrated Survey, Mobile Mapping, UAV In recent years, the GeCo Laboratory has undertaken numerous projects to digitalize vast and complex buildings; the specific nature of the different projects has resulted in a case-by-case approach, each time working on past experiences and updating not only the hardware and software tools but also the management and processing methods. This paper presents the workflow followed for the survey of the Fortress of Saint John the Baptist in Florence, an on-going interdisciplinary project. Presently Florence’s main trade fair congress centre, at the same time it hosts various buildings that bear witness to the fortress’s life-history, combining constructions from the Medici and Lorraine eras with recently built exhibition facilities. Now new research has been required due to the realization of new pavilions and the regeneration of the whole complex. This has included a critical survey, material testing, diagnostic investigations and stratigraphic analyses to define the building’s state of preservation. The working group comprises specialists from different institutions, amongst which the Italian Military Geographic Institute, the University of Florence, the National Research Council Institute for the Preservation and Enhancement of the Cultural Heritage, and the Florence City Council.

The increasing frequency and intensity of extreme weather events are accelerating the mechanisms of surface degradation of heritage buildings, and it is therefore appropriate to find automatic techniques to reduce the time and cost of monitoring and to support their planned conservation. A fully automated approach is presented here for the segmentation and classification of the architectural elements that make up one of the façades of Palazzo Pitti. The aim of this analysis is to provide tools for a more detailed assessment of the risk of detachment of parts of the pietraforte sandstone elements. Machine learning techniques were applied for the segmentation and classification of information from a DEM obtained via a photogrammetric drone survey. An unsupervised geometry-based classification of the segmented objects was performed using K-means for identifying the most vulnerable elements according to their shapes. The results were validated through comparing them with those obtained via manual segmentation and classification, as well as with studies carried out by experts in the field. The initial results, which can be integrated with non-geometric information, show the usefulness of drone surveys in the context of automatic monitoring of heritage buildings.