Lidar measurement of surface melt for a temperate Alpine glacier at the seasonal and hourly scales

This study shows how a new generation of terrestrial laser scanners can be used to investigate glacier surface ablation and other elements of glacial hydrodynamics at exceptionally high spatial and temporal resolution. The study area is an Alpine valley glacier, Haut Glacier d'Arolla, Switzerland. Here we use an ultra-long-range lidar RIEGL VZ-6000 scanner, having a laser specifically designed for measurement of snow- and ice-cover surfaces. We focus on two timescales: seasonal and daily. Our results show that a near-infrared scanning laser system can provide high-precision elevation change and ablation data from long ranges, and over relatively large sections of the glacier surface. We use it to quantify spatial variations in the patterns of surface melt at the seasonal scale, as controlled by both aspect and differential debris cover. At the daily scale, we quantify the effects of ogive-related differences in ice surface debris content on spatial patterns of ablation. Daily scale measurements point to possible hydraulic jacking of the glacier associated with short-term water pressure rises. This latter demonstration shows that this type of lidar may be used to address subglacial hydrologic questions, in addition to motion and ablation measurements.

An inertial sensor-based system for spatio-temporal analysis in classic cross-country skiing diagonal technique.

The present study proposes a method based on ski fixed inertial sensors to automatically compute spatio-temporal parameters (phase durations, cycle speed and cycle length) for the diagonal stride in classical cross-country skiing. The proposed system was validated against a marker-based motion capture system during indoor treadmill skiing. Skiing movement of 10 junior to world-cup athletes was measured for four different conditions. The accuracy (i.e. median error) and precision (i.e. interquartile range of error) of the system was below 6ms for cycle duration and ski thrust duration and below 35ms for pole push duration. Cycle speed precision (accuracy) was below 0.1m/s (0.005m/s) and cycle length precision (accuracy) was below 0.15m (0.005m). The system was sensitive to changes of conditions and was accurate enough to detect significant differences reported in previous studies. Since capture volume is not limited and setup is simple, the system would be well suited for outdoor measurements on snow.

Rockfall susceptibility assessment and remote geological mapping with LiDAR point clouds

Characterizing the geological features and structures in three dimensions over inaccessible rock cliffs is needed to assess natural hazards such as rockfalls and rockslides and also to perform investigations aimed at mapping geological contacts and building stratigraphy and fold models. Indeed, the detailed 3D data, such as LiDAR point clouds, allow to study accurately the hazard processes and the structure of geologic features, in particular in vertical and overhanging rock slopes. Thus, 3D geological models have a great potential of being applied to a wide range of geological investigations both in research and applied geology projects, such as mines, tunnels and reservoirs. Recent development of ground-based remote sensing techniques (LiDAR, photogrammetry and multispectral / hyperspectral images) are revolutionizing the acquisition of morphological and geological information. As a consequence, there is a great potential for improving the modeling of geological bodies as well as failure mechanisms and stability conditions by integrating detailed remote data. During the past ten years several large rockfall events occurred along important transportation corridors where millions of people travel every year (Switzerland: Gotthard motorway and railway; Canada: Sea to sky highway between Vancouver and Whistler). These events show that there is still a lack of knowledge concerning the detection of potential rockfalls, making mountain residential settlements and roads highly risky. It is necessary to understand the main factors that destabilize rocky outcrops even if inventories are lacking and if no clear morphological evidences of rockfall activity are observed. In order to increase the possibilities of forecasting potential future landslides, it is crucial to understand the evolution of rock slope stability. Defining the areas theoretically most prone to rockfalls can be particularly useful to simulate trajectory profiles and to generate hazard maps, which are the basis for land use planning in mountainous regions. The most important questions to address in order to assess rockfall hazard are: Where are the most probable sources for future rockfalls located? What are the frequencies of occurrence of these rockfalls? I characterized the fracturing patterns in the field and with LiDAR point clouds. Afterwards, I developed a model to compute the failure mechanisms on terrestrial point clouds in order to assess the susceptibility to rockfalls at the cliff scale. Similar procedures were already available to evaluate the susceptibility to rockfalls based on aerial digital elevation models. This new model gives the possibility to detect the most susceptible rockfall sources with unprecented detail in the vertical and overhanging areas. The results of the computation of the most probable rockfall source areas in granitic cliffs of Yosemite Valley and Mont-Blanc massif were then compared to the inventoried rockfall events to validate the calculation methods. Yosemite Valley was chosen as a test area because it has a particularly strong rockfall activity (about one rockfall every week) which leads to a high rockfall hazard. The west face of the Dru was also chosen for the relevant rockfall activity and especially because it was affected by some of the largest rockfalls that occurred in the Alps during the last 10 years. Moreover, both areas were suitable because of their huge vertical and overhanging cliffs that are difficult to study with classical methods. Limit equilibrium models have been applied to several case studies to evaluate the effects of different parameters on the stability of rockslope areas. The impact of the degradation of rockbridges on the stability of large compartments in the west face of the Dru was assessed using finite element modeling. In particular I conducted a back-analysis of the large rockfall event of 2005 (265'000 m3) by integrating field observations of joint conditions, characteristics of fracturing pattern and results of geomechanical tests on the intact rock. These analyses improved our understanding of the factors that influence the stability of rock compartments and were used to define the most probable future rockfall volumes at the Dru. Terrestrial laser scanning point clouds were also successfully employed to perform geological mapping in 3D, using the intensity of the backscattered signal. Another technique to obtain vertical geological maps is combining triangulated TLS mesh with 2D geological maps. At El Capitan (Yosemite Valley) we built a georeferenced vertical map of the main plutonio rocks that was used to investigate the reasons for preferential rockwall retreat rate. Additional efforts to characterize the erosion rate were made at Monte Generoso (Ticino, southern Switzerland) where I attempted to improve the estimation of long term erosion by taking into account also the volumes of the unstable rock compartments. Eventually, the following points summarize the main out puts of my research: The new model to compute the failure mechanisms and the rockfall susceptibility with 3D point clouds allows to define accurately the most probable rockfall source areas at the cliff scale. The analysis of the rockbridges at the Dru shows the potential of integrating detailed measurements of the fractures in geomechanical models of rockmass stability. The correction of the LiDAR intensity signal gives the possibility to classify a point cloud according to the rock type and then use this information to model complex geologic structures. The integration of these results, on rockmass fracturing and composition, with existing methods can improve rockfall hazard assessments and enhance the interpretation of the evolution of steep rockslopes. -- La caractérisation de la géologie en 3D pour des parois rocheuses inaccessibles est une étape nécessaire pour évaluer les dangers naturels tels que chutes de blocs et glissements rocheux, mais aussi pour réaliser des modèles stratigraphiques ou de structures plissées. Les modèles géologiques 3D ont un grand potentiel pour être appliqués dans une vaste gamme de travaux géologiques dans le domaine de la recherche, mais aussi dans des projets appliqués comme les mines, les tunnels ou les réservoirs. Les développements récents des outils de télédétection terrestre (LiDAR, photogrammétrie et imagerie multispectrale / hyperspectrale) sont en train de révolutionner l'acquisition d'informations géomorphologiques et géologiques. Par conséquence, il y a un grand potentiel d'amélioration pour la modélisation d'objets géologiques, ainsi que des mécanismes de rupture et des conditions de stabilité, en intégrant des données détaillées acquises à distance. Pour augmenter les possibilités de prévoir les éboulements futurs, il est fondamental de comprendre l'évolution actuelle de la stabilité des parois rocheuses. Définir les zones qui sont théoriquement plus propices aux chutes de blocs peut être très utile pour simuler les trajectoires de propagation des blocs et pour réaliser des cartes de danger, qui constituent la base de l'aménagement du territoire dans les régions de montagne. Les questions plus importantes à résoudre pour estimer le danger de chutes de blocs sont : Où se situent les sources plus probables pour les chutes de blocs et éboulement futurs ? Avec quelle fréquence vont se produire ces événements ? Donc, j'ai caractérisé les réseaux de fractures sur le terrain et avec des nuages de points LiDAR. Ensuite, j'ai développé un modèle pour calculer les mécanismes de rupture directement sur les nuages de points pour pouvoir évaluer la susceptibilité au déclenchement de chutes de blocs à l'échelle de la paroi. Les zones sources de chutes de blocs les plus probables dans les parois granitiques de la vallée de Yosemite et du massif du Mont-Blanc ont été calculées et ensuite comparés aux inventaires des événements pour vérifier les méthodes. Des modèles d'équilibre limite ont été appliqués à plusieurs cas d'études pour évaluer les effets de différents paramètres sur la stabilité des parois. L'impact de la dégradation des ponts rocheux sur la stabilité de grands compartiments de roche dans la paroi ouest du Petit Dru a été évalué en utilisant la modélisation par éléments finis. En particulier j'ai analysé le grand éboulement de 2005 (265'000 m3), qui a emporté l'entier du pilier sud-ouest. Dans le modèle j'ai intégré des observations des conditions des joints, les caractéristiques du réseau de fractures et les résultats de tests géoméchaniques sur la roche intacte. Ces analyses ont amélioré l'estimation des paramètres qui influencent la stabilité des compartiments rocheux et ont servi pour définir des volumes probables pour des éboulements futurs. Les nuages de points obtenus avec le scanner laser terrestre ont été utilisés avec succès aussi pour produire des cartes géologiques en 3D, en utilisant l'intensité du signal réfléchi. Une autre technique pour obtenir des cartes géologiques des zones verticales consiste à combiner un maillage LiDAR avec une carte géologique en 2D. A El Capitan (Yosemite Valley) nous avons pu géoréferencer une carte verticale des principales roches plutoniques que j'ai utilisé ensuite pour étudier les raisons d'une érosion préférentielle de certaines zones de la paroi. D'autres efforts pour quantifier le taux d'érosion ont été effectués au Monte Generoso (Ticino, Suisse) où j'ai essayé d'améliorer l'estimation de l'érosion au long terme en prenant en compte les volumes des compartiments rocheux instables. L'intégration de ces résultats, sur la fracturation et la composition de l'amas rocheux, avec les méthodes existantes permet d'améliorer la prise en compte de l'aléa chute de pierres et éboulements et augmente les possibilités d'interprétation de l'évolution des parois rocheuses.

Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.