Evaluation of the dynamic processes of a landslide with laser scanners and Bayesian methods

Abstract

This paper deals with the study of the dynamics of a landslide from two different but complementary point of views. The landslide is situated within the Miozza basin, an area of approximately 10.7 km2 located in the Alpine region of Carnia (Italy). In the first part of the paper, the macro-scale analysis of volumetric changes occurred after the reactivation of landslide in 2004 is addressed by using a two-epoch laser scanning surveys from airborne (ALS) and terrestrial (TLS) platforms. airborne laser scanning (ALS) data were collected in 2003 (before reactivation of the phenomenon) with an ALTM 3033 OPTECH sensor while terrestrial laser scanning (TLS) measurements were acquired in 2008 with a Riegl LMS-Z620. The second part of the paper deals with the study of dynamic processes of the landslide at micro-scale. To this aim, a global navigation satellite system (GNSS)-based monitoring network is analysed using a statistical approach to discriminate between measurement noise and possible actual displacements. This task is accomplished using both “classical” statistical testing and a Bayesian approach. The second method has been employed to verify some apparent vertical displacements detected by the classical test. As regards the first topic of the paper, achieved results show that long-range TLS instruments can be profitably used in mountain areas to provide high-resolution digital terrain models (DTMs) with superior quality and detail with respect to aerial light detection and ranging data only, even in areas with very low accessibility. Moreover, ALS- and TLS-derived DTMs can be combined each other in order to fill gaps in ALS data, mainly due to the complexity of terrain morphology, and to perform quite accurate calculations of volume changes due to landslide phenomenon. Finally, the outcomes of the application of Bayesian inference demonstrate the effectiveness of this method to better detect statistically significant displacements of a GNSS monitoring network points. However, the application of this method in the geodetic field requires the identification of a preferring direction of displacements, what is not always feasible in advance.