A low-cost landslide displacement activity assessment from time-lapse photogrammetry and rainfall data: Application to the Tessina landslide site

Acquiring useful and reliable displacement data from a complex landslide site is often a problem because of large, localized and scattered erosive processes and deformations; the inaccessibility of the site; the high cost of instrumentation and maintenance. However, these data are of fundamental importance not only to hazard assessments but also to understanding the processes at the basis of slope evolution. In this framework, time-lapse photogrammetry can represent a good compromise; the low accuracy is compensated for by the wide-ranging and dense spatial displacement information that can be obtained with inexpensive equipment. Nevertheless, when large displacement monitoring data sets become available, the problem becomes the choice of the most suitable statistical model to describe the probability of movement and adequately simplify the complexity of a scattered, intermittent, and spatially inhomogeneous displacement field. In this paper, an automated displacement detection method, which is based on the absolute image differences and digital correlations from a sequence of photos, was developed and applied to a photographic survey activity at the head of the Tessina landslide (northeastern Italy). The method allowed us to simplify and binarize the displacement field and to recognize the intermittent activity and the peculiar behaviours of different parts of the landslide, which were identified and classified by combining geomorphological and geological information. Moreover, for the first time, sliding correlations between these areas were quantitatively estimated using time-series-based binary logistic regression and the definition of a probability-based directed graph of displacement occurrence that connected the source zones to the lower depletion basin and the main collector channel. Using rainfall data, event-based logistic and Poisson regression models were applied to the upper zones of the landslide to estimate the probability of movement of each scarp and the persistence of the displacement as a result of certain rainfall events. The results of these statistical analyses highlighted the capability of this approach to quantitatively evaluate the pattern of displacement occurrences and to assess the evolution of a landslide site to gain insight into geomorphological processes. (C) 2016 Elsevier B.V. All rights reserved.