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Object-Based Geomorphological Mapping: Application on an Alpine Deep-Seated Gravitational Slope Deformation Contest (Germanasca Valley, Western Alps—Italy)

Articolo
Data di Pubblicazione:
2022
Abstract:
This research reports the use of a new method of geomorphological mapping in GIS environments, using a full-coverage, object-based method, following the guidelines of the new geomorphological legend proposed by ISPRA–AIGEO–CNG. This methodology is applied to a tributary valley of the Germanasca Valley, shaped into calcschist and greenschist, of the Piedmont Zone (Penninic Domain, Western Alps). The investigated sector is extensively affected by dep-seated gravitational slope deformation (DSGSD) that strongly influences the geological setting and the geomorphological features of the area. The mapping of these gravitational landforms in a traditional way creates some difficulties, essentially connected to the high density of information in the same site and the impossibility of specifying the relationships between different elements. The use of the full-coverage, object-based method instead is advantageous in mapping gravitational evidence. In detail, it allows for the representation of various landforms in the same sector, and their relationships, specifying the size of landforms, and with the possibility of multiscale representation in the GIS environment; and, it can progressively be update with the development of knowledge. This research confirms that the use of the full-coverage, object-based method allows for better mapping of the geomorphological features of DSGSD evidence compared to classical representation.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Deep-seated gravitational slope deformation; Full-coverage geomorphological mapping; Object-based method; Western Alps
Elenco autori:
Forno M.G.; Fubelli G.; Gattiglio M.; Taddia G.; Ghignone S.
Autori di Ateneo:
FORNO Maria Gabriella
FUBELLI Giandomenico
GHIGNONE STEFANO
Link alla scheda completa:
https://iris.unito.it/handle/2318/1838395
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/1838395/938463/Forno%20et%20al.,%202022%20Rodoretto%20applsci-12-00778-min.pdf
Pubblicato in:
APPLIED SCIENCES
Journal
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