Search

The reconnaissance, mapping and analysis of kinematic features of slow-moving landslides evolving along medium-deep sliding surfaces in urban areas can be a difficult task due to the presence and interactions of/with anthropic structures/infrastructures and human activities that can conceal morphological signs of landslide activity. The paper presents an integrated approach to investigate the boundaries, type of movement, kinematics and interactions (in terms of damage severity distribution) with the built environment of a roto-translational slow-moving landslide affecting the historic centre of Lungro town (Calabria region, southern Italy). For this purpose, ancillary multi-source data (e.g. geological-geomorphological features and geotechnical properties of geomaterials), both conventional inclinometer monitoring and innovative non-invasive remote sensing (i.e. A-DInSAR) displacement data were jointly analyzed and interpreted to derive the A-DInSAR-geotechnical velocity (DGV) map of the landslide. This result was then cross-compared with detailed information available on the visible effects (i.e. crack pattern and width) on the exposed buildings along with possible conditioning factors to displacement evolution (i.e. remedial works, sub-services, etc.). The full integration of multi-source data available at the slope scale, by maximizing each contribution, provided a comprehensive outline of kinematic-geometric landslide features that were used to investigate the damage distribution and to detect, if any, anomalous locations of damage severity and relative possible causes. This knowledge can be used to manage landslide risk in the short term and, in particular, is propaedeutic to set up an advanced coupled geotechnical-structural model to simulate both the landslide displacements and the behavior of interacting buildings and, therefore, to implement appropriate risk mitigation strategies over medium/long period. [ABSTRACT FROM AUTHOR]

In this paper, a systematic procedure to assess the feasibility of Advanced Differential Interferometric SAR (A-DInSAR) technique for landslide monitoring using SAR images acquired by Sentinel-1 sensors is presented. The methodology is named "Assessment of the advanced differentiaL interferometric synthetic aperture radar technique Feasibility for large scale lAndslide monitoring – ALFA" and it is structured in two main phases, which includes pre-processing and post-processing elaborations. The methodology was developed and tested in the Alpine sector of the Piedmont region in Italy, which represents a landslide prone area. In particular, ALFA represents a methodology based on previous algorithms available in the literature to assess the a-prior feasibility assessment and post-processing analysis of A-DInSAR data for landslide, which introduces three novel aspects such as (1) a systematic scheme suitable within regional practices; (2) the use of Sentinel-1 data and the development of (3) an index to take into account of the kind of distribution of the measuring points along the landslide. The approach was applied over an area extended about 5300 km2 affected by 5703 landslides mapped in the database of the Piedmont Region (Landslides information system in Piedmont—SIFRAP). Sentinel-1 images covering the period 2014–2018 were analysed. The results show the potential of the Sentinel-1 data for large-scale landslide monitoring. The developed methodology presents reliable tools that could be useful as feasibility for the use of Sentinel-1 data for landslide monitoring at regional and national scale. [ABSTRACT FROM AUTHOR]

The geometric and kinematic characterization of landslides affecting urban areas is a challenging goal that is routinely pursued via geological/geomorphological method and monitoring of ground displacements achieved by geotechnical and, more recently, advanced differential interferometric synthetic aperture radar (A-DInSAR) data. Although the integration of all the above-mentioned methods should be planned a priori to be more effective, datasets resulting from the independent use of these different methods are commonly available, thus making crucial the need for their standardized a posteriori integration. In this regard, the present paper aims to provide a contribution by introducing a procedure that, taking into account the specific limits of geological/geomorphological analyses and deep/surface ground displacement monitoring via geotechnical and A-DInSAR data, allows the a posteriori integration of the results by exploiting their complementarity for landslide characterization. The approach was tested in the urban area of Lungro village (Calabria region, southern Italy), which is characterized by complex geological/geomorphological settings, widespread landslides and peculiar urban fabric. In spite of the different level of information preliminarily available for each landslide as result of the independent use of the three methods, the implementation of the proposed procedure allowed a better understanding and typifying of the geometry and kinematics of 50 landslides. This provided part of the essential background for geotechnical landslide models to be used for slope stability analysis within landslide risk mitigation strategies. [ABSTRACT FROM AUTHOR]