3D terrain mapping and filtering from coarse resolution data cubes extracted from real-aperture 94 GHz radar

Funding: William D. Harcourt was funded by the Engineering and Physical Sciences Research Council (EPSRC; grant number: EP/R513337/1) and the Scottish Alliance for Geoscience, Environment and Society (SAGES).Accurate, high-resolution 3-D mapping of environmental terrain is critical in a range of disciplines. In this study, we develop a new technique, called the PCFilt-94 algorithm, to extract 3-D point clouds from coarse-resolution millimeter-wave radar data cubes and quantify their associated uncertainties. A technique to noncoherently average neighboring waveforms surrounding each AVTIS2 range profile was developed to reduce speckles and was found to reduce point cloud uncertainty by 13% at long range and 20% at short range. Furthermore, a Voronoi-based point cloud outlier removal algorithm was implemented, which iteratively removes outliers in a point cloud until the process converges to the removal of 0 points. Taken together, the new processing methodology produces a stable point cloud, which means that: 1) it is repeatable even when using different point cloud extraction and filtering parameter values during preprocessing and 2) is less sensitive to overfiltering through the point cloud processing workflow. Using an optimal number of ground control points (GCPs) for georeferencing, which was determined to be 3 at close ranges (3 km), point cloud uncertainty was estimated to be approximately 1.5 m at 1.5 km to 3 m at 3 km and followed a Lorentzian distribution. These uncertainties are smaller than those reported for other close-range radar systems used for terrain mapping. The results of this study should be used as a benchmark for future application of millimeter-wave radar systems for 3-D terrain mapping.Peer reviewe

Analysis of filtering techniques for investigating landslide-induced topographic changes in the Oetz Valley (Tyrol, Austria)

Landslides endanger settlements and infrastructure in mountain areas across the world. Monitoring of landslides is therefore essential in order to understand and possibly predict their behavior and potential danger. Terrestrial laser scanning has proven to be a successful tool in the assessment of changes on landslide surfaces due to its high resolution and accuracy. However, it is necessary to classify the 3D point clouds into vegetation and bare-earth points using filtering algorithms so that changes caused by landslide activity can be quantified. For this study, three classification algorithms are compared on an exemplary landslide study site in the Oetz valley in Tyrol, Austria. An optimal set of parameters is derived for each algorithm and their performances are evaluated using different metrics. The volume changes on the study site between the years 2017 and 2019 are compared after the application of each algorithm. The results show that (i) the tested filter techniques perform differently, (ii) their performance depends on their parameterization and (iii) the best-performing parameterization found over the vegetated test area will yield misclassifications on non-vegetated rough terrain. In particular, if only small changes have occurred the choice of the filtering technique and its parameterization play an important role in estimating volume changes.publishedVersio

94 GHz Radar Backscatter Characteristics of Alpine Glacier Ice

Acknowledgments William D. Harcourt would like to thank PhD studentship funding from SAGES and EP281 SRC (grant number: EP/R513337/1). Funding for this study was obtained from the Scot282 tish Alliance for Geoscience, Environment and Society (SAGES) Small Grant Scheme. We would like to thank the staff at the Rhˆonegletscher Eisgrotte Cafe for enabling en284 trance to the field site and supporting the field activities, as well as the VAW Glaciol285 ogy Group and Glacier Monitoring in Switzerland groups for providing aerial photogram metry data over Rhˆonegletscher. Thanks also to Josu´e Gehring, Alexis Berne and Etienne Vignon for assisting with collection and delivery of our equipment at Ecole Polytechnique D´ed´erale de Lausanne (EPFL).Peer reviewedPublisher PD

Millimetre-wave radar observations of glacier calving at Hansbreen (Svalbard) correlated with TLS, time-lapse camera images and seismic records

Publisher PD

Laetoli Footprints Preserve Earliest Direct Evidence of Human-Like Bipedal Biomechanics

Background Debates over the evolution of hominin bipedalism, a defining human characteristic, revolve around whether early bipeds walked more like humans, with energetically efficient extended hind limbs, or more like apes with flexed hind limbs. The 3.6 million year old hominin footprints at Laetoli, Tanzania represent the earliest direct evidence of hominin bipedalism. Determining the kinematics of Laetoli hominins will allow us to understand whether selection acted to decrease energy costs of bipedalism by 3.6 Ma. Methodology/Principal Findings Using an experimental design, we show that the Laetoli hominins walked with weight transfer most similar to the economical extended limb bipedalism of humans. Humans walked through a sand trackway using both extended limb bipedalism, and more flexed limb bipedalism. Footprint morphology from extended limb trials matches weight distribution patterns found in the Laetoli footprints. Conclusions These results provide us with the earliest direct evidence of kinematically human-like bipedalism currently known, and show that extended limb bipedalism evolved long before the appearance of the genus Homo. Since extended-limb bipedalism is more energetically economical than ape-like bipedalism, energy expenditure was likely an important selection pressure on hominin bipeds by 3.6 Ma

Snapshots of human anatomy, locomotion, and behavior from Late Pleistocene footprints at Engare Sero, Tanzania

Fossil hominin footprints preserve data on a remarkably short time scale compared to most other fossil evidence, offering snapshots of organisms in their immediate ecological and behavioral contexts. Here, we report on our excavations and analyses of more than 400 Late Pleistocene human footprints from Engare Sero, Tanzania. The site represents the largest assemblage of footprints currently known from the human fossil record in Africa. Speed estimates show that the trackways reflect both walking and running behaviors. Estimates of group composition suggest that these footprints were made by a mixed-sex and mixed-age group, but one that consisted of mostly adult females. One group of similarly oriented trackways was attributed to 14 adult females who walked together at the same pace, with only two adult males and one juvenile accompanying them. In the context of modern ethnographic data, we suggest that these trackways may capture a unique snapshot of cooperative and sexually divided foraging behavior in Late Pleistocene humans