In the analysis of the temporal evolution of landslides and of related hydrogeological hazards, Terrestrial Laser Scanning seems to be a very suitable technique for morphological description and displacement analysis. In this note we present some procedures designed to solve specific issues related to monitoring. A particular attention has been devoted to data georeferencing, both during survey campaigns and while performing statistical data analysis. The proper interpolation algorithm for DEM generation has been chosen taking into account the features of the landslide morphology and of the acquired datasets. For a detailed analysis of the different dinamics of the hillslope, we identified some areas with homogeneous behaviour applying in a GIS environment a sort of rough segmentation to the grid obtained differentiating two surfaces. This approach has allowed a clear identification of ground deformations, obtaining detailed quantitative information on surficial displacements. These procedures have been applied to a case study on a large landslide of about 10 hectares, located in Italy, which recently has severely damaged the national railway line. Landslide displacements have been monitored with TLS surveying for three years, from February 2010 to June 2012. Here we report the comparison results between the first and the last survey

Abstract:Terrestrial laser scanning (TLS) is a relatively new, versatile, and efficient technology for landslide monitoring. The evaluation of uncertainty of the surveyed data is not trivial because the final accuracy of the point position is unknown. An a priori evaluation of the accuracy of the observed points can be made based on both the footprint size and of the resolution, as well as in terms of effective instantaneous field of view (EIFOV). Such evaluations are surely helpful for a good survey design, but the further operations, such as cloud co-registration, georeferencing and editing, digital elevation model (DEM) creation, and so on, cause uncertainty which is difficult to evaluate. An assessment of the quality of the survey can be made evaluating the goodness of fit between the georeferenced point cloud and the terrain model built using it. In this article, we have considered a typical survey of a landsliding slope. We have presented an a priori quantitative assessment and we eventually analyzed how good the comparison is of the computed point cloud to the actual ground points. We have used the method of cross-validation to eventually suggest the use of a robust parameter for estimating the reliability of the fitting procedure. This statistic can be considered for comparing methods and parameters used to interpolate the DEM. Using kriging allows one to account for the spatial distribution of the data (including the typical anisotropy of the survey of a slope) and to obtain a map of the uncertainties over the height of the grid nodes. This map can be used to compute the estimated error over the DEM-derived quantities, and also represents an "objective" definition of the area of the survey that can be trusted for further use.

This paper addresses the problems arising from the use of data acquired with two different remote sensing techniques-high-resolution satellite imagery (HRSI) and terrestrial laser scanning (TLS)-for the extraction of digital elevation models (DEMs) used in the geomorphological analysis and recognition of landslides, taking into account the uncertainties associated with DEM production. In order to obtain a georeferenced and edited point cloud, the two data sets require quite different processes, which are more complex for satellite images than for TLS data. The differences between the two processes are highlighted. The point clouds are interpolated on a DEM with a 1 m grid size using kriging. Starting from these DEMs, a number of contour, slope, and aspect maps are extracted, together with their associated uncertainty maps. Comparative analysis of selected landslide features drawn from the two data sources allows recognition and classification of hierarchical and multiscale landslide components. Taking into account the uncertainty related to the map enables areas to be located for which one data source was able to give more reliable results than another. Our case study is located in Southern Italy, in an area known for active landslides.

Terrestrial laser scanning (TLS) has proven to be a very effective technique for landslides monitoring, even if some critical issues exist for providing highly reliable results. This chapter presents the methodology adopted in performing four surveys, carried out over three years on a large slump landslide in order to get effectively comparable data. The first problem concerns the setting up of the reference system, which has been realized by means of global navigation satellite system permanent stations ETRF00 datum. This solution was able to maximize the stability over time even at the expense of a slightly lower precision, which was, however, in the order of 1-2 cm with data recorded during the whole duration of TLS survey. An assessment of geo-referencing accuracy was carried out with respect to the only stable artifact present in the landslide area. This check pointed out that in the central part of the point cloud the repeatability between different surveys was slightly greater than 5 cm. To ensure the quality of the obtained multitemporal digital terrain models (DTM's) over the entire region of interest, the choice of the interpolation algorithm has been performed and verified with a cross-validation method on the basis of a sample extracted from the data set. To detect the kinematics of the landslide in its several parts, both the DTM's and profiles have been used, which have proven to be particularly useful for the interpretation of details. After the localization of various landslide bodies (keeping into account slope and aspect maps derived from the DTM), the evaluation of the volumes mobilized over time has been carried out by

ABSTRACT:In order to reliably detect changes in the surficial morphology of a landslide, measurements performed at the different epochs being compared have to comply with certain characteristics such as allowing the reconstruction of the surface from acquired points and a resolution sufficiently high to provide a proper description of details. Terrestrial Laser Scanning survey enables to acquire large amounts of data and therefore potentially allows knowing even small details of a landslide. By appropriate additional field measurements, point clouds can be referenced to a common reference systemwith high accuracy,so thatscans effectively share the samesystem.In this note we present the monitoring of a large landslide by two surveys carried out two years apart from each other.The adopted reference frame consists of a network of GNSS (Global Navigation Satellite Systems) permanent stations that constitutes a system of controlled stability over time.Knowledge of the shape of the surface comes from the generation of a DEM (Digital Elevation Model).Some algorithms are compared and the analysis is performed by means of the evaluation of some statistical parameters using cross-validation.In general, evaluation of mass displacements occurred between two surveys is possible differencing the corresponding DEMs, but then arises the need to distinguish the different behaviors of the various landslide bodies that could be present among the slope.Here landslide bodies" identification has been carried out considering geomorphological criteria, making also use of DEM derived products, such as contour maps, slope and aspect maps.