Integration of 3D surveying approaches for critical infrastructure digital twins in natural hazard-prone scenarios

The fragile geomorphological context of Italy sets a variety of natural challenges, ranging from seismic to hydrogeological risk. In such a complex territory, documenting the conditions of infrastructures is crucial for planning adequate strategies of maintenance through 3D modelling for structural analysis and digital twins’ implementation of structures like dams (Pagliari et al., 2016) or bridges (Gaspari et al., 2022). Geomatics, through periodical surveys using state-of-the-art technologies, reconstruct accurate 3D models of structures that results in the generation of dense pointclouds from which polygon meshes can be derived as well as in the model integration in Building Information Modeling (BIM) or Finite Element Method (FEM) environments for the computation of simulations and deformation monitoring or structural health assessment analysis in support of decision making.

Such data are generated through different approaches. A traditional methodology first implies the materialization and measurement of a topographic network in a local system with a total station and its subsequent georeferencing in a global coordinate reference system through a roto-translation based on Global Navigation Satellite System observations of ground control points. In the same framework, scans for the acquisition of dense pointclouds are defined through the adoption of a terrestrial laser scanner (TLS). Hence, the execution of planned drone flights, with nadiral and side view of the structure and its surrounding environment, serving as input for the generation of photogrammetric cloud through a robust Structure from Motion data processing.

Implementing open-source WebGL solutions like Potree supports the digital twin and data sharing with audiences of different technical backgrounds, committers concerned with the adoption of a monitoring platform for integrating products in different format as well as experts with non-geomatics expertise interested in further analysis of collected data through computer vision and deep learning approches that enrich the existent documentation. With a user-friendly interactive web platforms users are able to access the 3D model, make measurements and execute simple processing operation like cross-sections and clipping (e.g. https://labmgf.dica.polimi.it/piacenzacs/lugagnano/).

Since 2019, the dams of the Sila mountains in the Calabria region represented the case study for testing the described integrated approach. The present work concerns the integration of data from different sensors (TLS for indoor and outdoor environment, photogrammetric images and lidar from drone) for the generation of the digital twin of the arcuate-plan gravity dam of Trepidò. The dam digital twin of the dam and adjacencies consists of a pointcloud of 2594370 points, with adaptive density and average accuracy of 1-2 cm for the structure and 10 cm for the downstream vegetated sediment. It can be used to increase knowledge of the structure (built in 1930) and for structural analysis.

 

Bibliography:

 

Gaspari, F., Ioli, F., Barbieri, F., Belcore, E., and Pinto, L. (2022): Integration of UAV-LiDAR and UAV-photogrammetry for infrastructure monitoring and bridge assessment, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 995–1002, doi.org/10.5194/isprs-archives-XLIII-B2-2022-995-2022.

Pagliari, D., Rossi, L., Passoni, D., Pinto, L., de Michele, C., and Avanzi, F. (2016). Measuring the volume of flushed sediments in a reservoir using multi-temporal images acquired with UAS, Geomatics, Natural Hazards and Risk, 8(1), 150–166, doi.org/10.1080/19475705.2016.1188423