The design of a tunnel must be solidly based on the knowledge of the territory. An optimization of the investigation process is strongly required in order to obtain complete and reliable data for the design. The fast development of remote sensing technologies and the affordability of their products have contributed to extensively prove their benefits as supports for investigation, encouraging the spreading of automatic or semi-automatic methods for regional scale surveys. Similarly, considering the scale of the rock outcrop, photogrammetric and laser scanner techniques are well-established techniques for the representation of the geometrical features of rock masses: The benefits of non-contact surveys in terms of safety and time consumption are acknowledged not only by the research community but also by experts and companies. Unfortunately, in most cases data obtained at the different scales of investigations are only partially integrated or compared, probably due to a missing exchange of knowledge among experts of different fields (e.g. geologists and geotechnical engineers). The authors propose a multiscale approach for the optimization of the investigation process: starting from the regional scale, the aim is to obtain data than can be useful not only to plan more detailed surveys, but also to make previsions on the potential discontinuity sets that could be present in the rock masses subject to the excavation. A methodological process is proposed and illustrated by means of an application to a case study. Preliminary results are discussed in order to highlight the potentiality of this method and its limitations.
The design of a tunnel must be solidly based on the knowledge of the geological, hydrogeological and morphological characteristics of the territory. The bigger the structure, the larger the area to be investigated, the greater the number of surveys and tests to be performed in order to examine in depth all the relevant features: therefore, an optimization of the investigation process is strongly required in order to obtain complete and reliable data for the design of the infrastructure.
