Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study

Abstract

Abstract. In the paper we analyse a multi-date landslide inventory prepared for a mountainous area affected by several landslide types with different degrees of activity, we attempt to quantify the uncertainties associated to the mapping, we measure the evolution of morphological indicators and estimate landslide activity and temporal occurrence. The inventory, covering the period 1956-2010, is prepared for the middle section of the Ubaye valley (southern French Alps) based on the analysis of multi-source documents (geomorphological maps, historical reports of landslide events, field surveys, orthophotographs and SAR (synthetic aperture radar) satellite images). The uncertainties derived from the expert interpretation of different sources of information, the landslide morphological features and the affected land covers are taken into account in relation to the source documents.Morphological indicators are calculated to describe quantitatively the evolution of the landslides (length, area, relative elevation, runout distance). Frequency-area density functions are computed to estimate the changes in the landslide distributions and a Poisson model is used to estimate the probability of reactivation of the observed landslides and the occurrence of new failures. The proposed multi-date inventory and the associated statistics provide additional information to the event catalogue managed by the local policy makers.

The geographical prerequisites for the identification and prevention of dangerous geomorphological processes in the mountain geosystems of the Alpine-Himalayan belt (on the example of the Major Caucasus of Azerbaijan)

“…Methods and materials. Researchers of different countries have developed and continue to develop techniques for preventing landslides, which calculate the risks of occurrence of this or that phenomenon in territories with different natural conditions (Petrascheck and Hazard, 2003;Yafiazova, 2009;Seversky et al, 2010;Lee et al, 2008;Schlögel et al, 2015;Duong et al, 2013;Ardizzone et al, 2002;Baynes et al, 2002;Brardinoni et al, 2003;Corominas et al, 2014;Malamud et al, 2004;Singhroy and Molch, 2004;Abu-Zeid et al, 2003;Inaba, 2003;Mills, 2003;Paramonov, 2005).…”

“…After analyzing a number of techniques used to assess the landslide hazards (Seversky et al, 2010;Lee, 2006;Bobrovich, 2008;Schlögel et al, 2015;Duong et al, 2013;Ardizzone et al, 2002;Baynes et al, 2002;Brardinoni et al, 2003;Corominas et al, 2015;Malamud et al, 2004;Singhroy and Molch, 2004), the conclusion was made that most of them had their flaws. Deterministic methods of analysis (Bobrovich, 2008) based on estimated values of stability coefficients often show results that do not correspond to reality due to the lack of initial engineering and geological data.…”

Landslide Susceptibility Assessment by EPBM (Expert Physically Based Model): Strategy of Calibration in Complex Environment

“…The characteristics and the activity of these instabilities have been studied during the last twenty years by several research teams (Maquaire et al, 2003;Malet et al, 2005;Thiery et al, 2007;Schlögel et al, 2015). On the basis of different information source (Thiery et al, 2007;Schlögel et al, 2015) and a diachronic air photograph interpretation between 1974 and 2004 coupling with field observations, a landslide inventory was compiled at 1:10,000 scale.…”

“…On the basis of different information source (Thiery et al, 2007;Schlögel et al, 2015) and a diachronic air photograph interpretation between 1974 and 2004 coupling with field observations, a landslide inventory was compiled at 1:10,000 scale. The boundaries of landslides are digitized in two zones: (i) the landslide triggering zone (LTZ) and (ii) the landslide accumulation zone (LAZ, Fig.…”

Multi-Temporal X-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy)

“…The launches of new generations of optical (e.g., Geoeye-1, WorldView-2, Pleiades 1A and 1B, SPOT5, 6 and 7, Formosat-2 and Kompsat-2, Sentinel-2) and radar (e.g., TerraSAR-X, COSMO-SkyMed, Sentinel-1) satellites with short repeat-pass cycles and high spatial resolutions resulted in better capabilities to acquire data over wide areas shortly after major landslide triggering events [25][26][27][28] and to monitor them at regular intervals [29,30]. In particular, radar interferometry is today frequently applied to landslide detection and monitoring of ground-deformations and landslide processes [31][32][33][34][35][36][37][38]. Multi-temporal Interferometry (MTI) techniques use large stacks composed of many Synthetic Aperture Radar (SAR) images (i.e., >20) acquired with the same geometry and exploit the redundant information of phase difference, thus removing much inherent noise (in particular reducing the atmospheric contribution called Atmospheric Phase Screen (APS)) for a better accuracy of the phase difference due to the ground displacement [39].…”