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.

The increasing demand for 3D digital models has spurred the rapid evolution of technologies to acquire, process, and disseminate 3D data of physical artifacts. Current scanners meet building surveying needs, prompting the exploration of closed systems with multiple sensors, custom accessories, control systems, and varied data processing approaches. While efficient in specific conditions, these systems require careful consideration of factors like technical requirements, environmental conditions, and the intended use of the final model. This article compares a static terrestrial laser scanner (TLS) and a portable mobile mapping system (PMMS) for documenting built heritage, focusing on the City Hall of Montecatini Terme in Italy. The Leica Geosystems RTC360 scanner provides quick scanning times and pre-alignment during fieldwork, reducing post-processing efforts. The Leica BLK2GO, belonging to the PMMS family, utilizes laser SLAM, visual SLAM, and inertial IMU measurements for rapid large-area documentation. The comparison assesses accuracy, completeness, and detail recognition, revealing that both systems are suitable for heritage documentation requiring centimetre-level accuracy. However, differences in point density and roughness indicate that the RTC360 may be better for intricate details. The BLK2GO excels in efficiency but is more oriented toward general representations at the architectural scale. This study emphasizes the importance of evaluating different methodologies based on project objectives and desired levels of detail, providing insights into the strengths and limitations of each system for diverse applications in heritage documentation.

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.

The democratization and accessibility of low-cost devices for image acquisition and the development of highly automated procedures for orientation and dense image matching allow almost every person to be a potential producer of photogrammetric models. The diffusion of image-based technologies to produce 3D models amongst wider audiences entails however some risks, as the lack of critical awareness of the final quality of the outputs. Information and education about potentialities and limitations of reality-based digitization by photogrammetry may help spreading procedures and methods for the correct use of this technology. This paper presents the results of one of the funded projects within the 2018 ISPRS Capacity Building Initiatives “Education and training resources on digital photogrammetry”. The production of multimedia material for supporting smart educational teaching and learning approaches will be reported, as well as experiences on their application on case studies. Blended innovative teaching and learning pedagogical approaches have been tested, as Flipped Classroom (FC), Learning-by-doing (LBD), Collaborative Learning (CL), and Challenge-Based Learning (CBL), supported by multimedia tools for capacity-building and knowledge transfer. The implementation of multimedia materials for supporting teaching strategies resulted in the production of updated and engaging resources, as videos, tutorials, and datasets to be used during courses, workshops, and seminars targeted to different user groups. The combination of teaching strategies and multimedia supporting materials were tested within national and international projects, from academic courses to complete non-experts, from activities on the field to online and distance learning.

The Laboratory of Geomatics for Environment and Conservation of Cultural Heritage (GECO – University of Florence) has been involved since 2011 in a process of technological transfer in collaboration with the Oficina del Historiador de La Ciudad de La Habana (OHcH). The know-how transfer concerning geomatics techniques for documentation and surveying of cultural heritage is of fundamental interest for the principal Institution designated to the protection of Havana historical centre. The first project (2011–2014) was mainly focused on the formation of specialized technicians from OHcH in the use of Terrestrial Laser Scanner (TLS), for documentation purposes of monumental and architectonical heritage. The ongoing project, INNOVA CUBA – “International and intersectoral intervention for the safeguard of the cultural heritage of the country” started in 2017, is funded by AICS – Italian Agency for Development Cooperation and coordinated by ARCS – Culture Solidali. The introduction of digital close-range photogrammetry represents the natural progression of this educational process, thus implementing the range of innovative surveying technologies available, in terms of instruments, software and technical know-how. The two-weeks training experience in Havana (2018) provided the participants, technical staff from OHcH and other institutions, all the necessary knowledge to be autonomously able to choose the suitable surveying technique, depending on object characteristics and on available devices, to correctly plan the survey and evaluate its metric quality. A final workshop, for a wider audience, was the opportunity to introduce future crowdsourcing photogrammetric activities, to improve the sensitivity and engagement of local community towards heritage protection and valorisation processes.