Abstract
Abstract. Slow moving deep-seated gravitational slope deformations are threatening infrastructure and economic wellbeing in mountainous areas. Accelerating landslides may end up in a catastrophic slope failure in terms of rapid rock avalanches. Continuous landslide monitoring enables the identification of critical acceleration thresholds, which are required in natural hazard management. Among many existing monitoring methods, laser scanning is a cost effective method providing 3D data for deriving three dimensional and areawide displacement vectors at certain morphological structures travelling on top of the landslide. Comparing displacements between selected observation periods allows the spatial interpretation of landslide acceleration or deceleration. This contribution presents five laser scanning datasets of the active Reissenschuh landslide (Tyrol, Austria) acquired by airborne laser scanning (ALS), terrestrial laser scanning (TLS) and Unmanned aerial vehicle Laser Scanning (ULS) sensors. Three observation periods with acquisition dates between 2008 and 2018 are used to derive area-wide displacement vectors. To ensure a most suitable displacement derivation between ALS, TLS and ULS platforms, an analysis investigating point cloud features within varying search radii is carried out, in order to identify a neighbourhood where common surfaces are represented platform independent or differences between the platforms are minimized. Consequent displacement vector estimation is done by ICP-Matching using morphological structures within the high resolution TLS and ULS point cloud. Displacements from the lower resolution ALS point cloud and TLS point cloud were determined using a modified version of the well-known image correlation (IMCORR) method working with point cloud derived shaded relief images combined with digital terrain models (DTM). The interplatform compatible analyses of the multi-temporal laser scanning data allows to quantify the area-wide displacement patterns of the landslide. Furthermore, changes of these displacement patterns over time are assessed area-wide. Spatially varying areas of landslide acceleration and deceleration in the order of ±15 cm a−1 between 2008 and 2017 and an area wide acceleration of up to 20 cm a−1 between 2016 and 2018 are identified. Continuing the existing time series with future ULS acquisitions may enable a more complete and detailed displacement monitoring using entirely represented objects within the point clouds.
Highlights
Monitoring the movement of deep seated gravitational slope deformations (DSGSDs) is an important tool to detect landslide acceleration and potential slope collapses leading to catastrophic rock avalanches (Carlaet al., 2017, Ostermann and Sanders, 2017)
The objectives of this study are (i) to describe the major differences of point clouds obtained from different laser scanning platforms, (ii) to identify and apply an interplatform compatible method to derive landslide displacements from different laser scanning platforms and (iii) to present and interpret a time series of landslide displacements obtained from an integration of multi-platform laser scanning data indicating landslide movement patterns between different observation periods
Occlusions are quantified as coverage and the spatial resolution usually specified as point spacing are two main parameters affecting the quality of object representation
Summary
Monitoring the movement of deep seated gravitational slope deformations (DSGSDs) is an important tool to detect landslide acceleration and potential slope collapses leading to catastrophic rock avalanches (Carlaet al., 2017, Ostermann and Sanders, 2017). Vegetation penetrating multi-temporal laser scanning has become a cost-efficient data acquisition technique for area-wide change detection analyses (Wujanz et al, 2018) and landslide displacement analyses (Fey et al, 2015, Pfeiffer et al, 2018). Surface information of each epoch may be assessed with a different acquisition platform demanding the application of interplatform compatible displacement estimation techniques (Corsini et al, 2009, Zieher et al, 2018, Young et al, 2010, Ghuffar et al, 2013). Different laser scanning platforms implicate certain advantages or disadvantages considering data properties or acquisition effort. This contribution presents an existing time series covering 10 years of airborne laser scanning (ALS) and terrestrial laser scanning (TLS) data which is recently continued with Unmanned
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