Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4129-2022
https://doi.org/10.5194/essd-14-4129-2022
Data description paper
 | 
07 Sep 2022
Data description paper |  | 07 Sep 2022

A new digital lithological map of Italy at the 1:100 000 scale for geomechanical modelling

Francesco Bucci, Michele Santangelo, Lorenzo Fongo, Massimiliano Alvioli, Mauro Cardinali, Laura Melelli, and Ivan Marchesini

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Revised manuscript accepted for ESSD
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Cited articles

Alvarez, W. and Shimabukuro, D. H.: The geological relationships between Sardiniaand Calabria during Alpine and Hercynian times, Ital. J. Geosci., 128, 257–282, https://doi.org/10.3301/IJG.2009.128.2.257, 2009. 
Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., and Guzzetti, F.: Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling, Geosci. Model Dev., 9, 3975–3991, https://doi.org/10.5194/gmd-9-3975-2016, 2016. 
Alvioli, M., Guzzetti, F., and Marchesini, I.: Parameter-free delineation of slope units and terrain subdivision of Italy, Geomorphology, 358, 107124, https://doi.org/10.1016/j.geomorph.2020.107124, 2020. 
Alvioli, M., Santangelo, M., Fiorucci, F., Cardinali, M., Marchesini, I., Reichenbach, P., Rossi, M., Guzzetti, F., and Peruccacci, S.: Rockfall susceptibility and network-ranked susceptibility along the Italian railway, Eng. Geol., 293, 106301, https://doi.org/10.1016/j.enggeo.2021.106301, 2021. 
Amanti, M., Battaglini, L., Campo, V., Cipolloni, C., Congi, M. P., Conte, G., Delogu, D., Ventura, R., and Zonetti, C.: La carta litologica d'italia alla scala 1:100 000, in: Atti della 11a Conferenza Nazionale ASITA, Turin, Italy, 6–9 November 2007, http://atti.asita.it/Asita2007/Pdf/119.pdf (last access: 14 January 2022), 2007. 
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The paper describes a new lithological map of Italy at a scale of 1 : 100 000 obtained from classification of a digital database following compositional and geomechanical criteria. The map represents the national distribution of the lithological classes at high resolution. The outcomes of this study can be relevant for a wide range of applications, including statistical and physically based modelling of slope stability assessment and other geoenvironmental studies.
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