 |
| Titel |
Agglomerative hierarchical cluster method to analyze landslide displacements and assess risk scenarios |
| VerfasserIn |
Giulia Bossi, Stefano Crema, Matteo Mantovani, Luca Schenato, Marco Cavalli, Gianluca Marcato, Simone Frigerio, Alessandro Pasuto |
| Konferenz |
EGU General Assembly 2017
|
| Medientyp |
Artikel
|
| Sprache |
en
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250140939
|
| Publikation (Nr.) |
 EGU/EGU2017-4394.pdf |
|
|
|
|
|
| Zusammenfassung |
| In the Rotolon catchment (eastern Italian Alps) a large Deep-seated Gravitational Slope
Deformation (DGSD) induces secondary phenomena that are threatening the local
population. In 2010 a mass of 340.000 m3 detached from the frontal part of the DGSD and
then flow into the draining channel in the form of a debris flow, damaging a bridge and almost
over-flooding, endangering the houses located 3 km downstream. For this reason, an
Automated Total Station (ATS) has been installed in 2012 to monitor surface displacements
so as to identify the most active regions of the slope in order to estimate the volume of
material that could be mobilized in the next paroxysmal event and to assess the related risk.
42 benchmarks (5 stable control points and 37 on the active slope) have been monitored for
two periods: the first one of 22 months between 2012 and 2014 and the second one for 12
months between 2015 and 2016. Analyzing the time series of displacements with the
agglomerative hierarchical cluster method calculated with a simple single linkage
algorithm, groups of similarly moving benchmarks have been clustered. For these
groups the trend of acceleration and deceleration of displacements follows similar
patterns. Even though the methodology does not take into account the position of
the benchmarks, matching patterns are found in contiguous benchmarks within
the groups, thus confirming the effectiveness of the approach. The possibility to
identify areas with homogeneous behavior is fundamental to delineate the volume of
possible new debris flow phenomena and therefore to produce reliable risk scenarios. |
|
|
|
|
|
|