Studies and realization of a near real time geological network monitoring system on the Idro landslide (BS)

The network monitoring system, which has been in operation on the Idro landslide, for several years, shows an average movement of 3 cm to 6 cm a year and defines a displacement area of approximately 270.000 m2. The volume estimation of the landslide is about 5 million cubic meters. The acceleration of the landslide movement is related to the raising of the water table which is linked to increased rainfall. Due to the necessity for a reliable early warning system, focus has been put on transmission reliability and the accuracy and precision of the sensors that have been positioned. Sensors used for motion checking are accurate and precise, giving coherent values between the different types of instruments. Numerous sensors have been set up in order to guarantee a redundancy for both number (we have installed various types of similar kinds of instruments) and variety (we have installed two or three kinds of instruments) of instruments while controlling deep and surface conditions. The analogy between deep soil data values and surface data values show us how movements deep soil data values and surface data values show us how movements seem to be located on only one surface being monitored by real-time deep inclinometers.

The network monitoring system, which has been in operation on the Idro landslide, for several years, shows an average movement of 3 cm to 6 cm a year and defines a displacement area of approximately 270.000 m2. The volume estimation of the landslide is about 5 million cubic meters. The acceleration of the landslide movement is related to the raising of the water table which is linked to increased rainfall. Due to the necessity for a reliable early warning system, focus has been put on transmission reliability and the accuracy and precision of the sensors that have been positioned. Sensors used for motion checking are accurate and precise, giving coherent values between the different types of instruments. Numerous sensors have been set up in order to guarantee a redundancy for both number (we have installed various types of similar kinds of instruments) and variety (we have installed two or three kinds of instruments) of instruments while controlling deep and surface conditions. The analogy between deep soil data values and surface data values show us how movements deep soil data values and surface data values show us how movements seem to be located on only one surface being monitored by real-time deep inclinometers.


ISSN 1121-9041

CiteScore:
2020: 3.8
CiteScore measures the average citations received per peer-reviewed document published in this title.
CiteScore values are based on citation counts in a range of four years (e.g. 2016-2019) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2016 —19).
Source Normalized Impact per Paper (SNIP):
2019: 1.307
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR)
2019: o.657
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal's impact.
Journal Metrics: CiteScore: 1.0 , Source Normalized Impact per Paper (SNIP): 0.381 SCImago Journal Rank (SJR): 0.163

Supported by


Edited by


GEAM - Associazione Georisorse e Ambiente c/o Dipartimento di Ing.dell’Ambiente, del Territorio e delle infrastrutture Politecnico di Torino
Copyright @ GEAM - Designed by DESIGN GANG - Privacy Policy