9 research outputs found
High-Frequency 3d Geomorphic Observation Using Hourly Terrestrial Laser Scanning Data Of A Sandy Beach
Geomorphic processes occur spatially variable and at varying magnitudes, frequencies and velocities, which poses a great challenge to current methods of topographic change analysis. For the quantification of surface change, permanent terrestrial laser scanning (TLS) can generate time series of 3D point clouds at high temporal and spatial resolution. We investigate how the temporal interval influences volume change observed on a sandy beach regarding the temporal detail of the change process and the total volume budget, on which accretion and erosion counteract. We use an hourly time series of TLS point clouds acquired over six weeks in Kijkduin, the Netherlands. A raster-based approach of elevation differencing provides the volume change over time per square meter. We compare the hourly analysis to results of a three- and six-week observation period. For the larger period, a volume increase of 0.3 m³/m² is missed on a forming sand bar before it disappears, which corresponds to half its volume. Generally, a strong relationship is shown between observation interval and observed volume change. An increase from weekly to daily observations leads to a five times larger volume change quantified in total. Another important finding is a temporally variable measurement uncertainty in the 3D time series, which follows the daily course of air temperature. Further experiments are required to fully understand the effect of atmospheric conditions on high-frequency TLS acquisition in beach environments. Continued research of 4D geospatial analysis methods will enable automatic identification of dynamic change and improve the understanding of geomorphic processes.Optical and Laser Remote SensingCoastal Engineerin
Characterization of morphological surface activities derived from near-continuous terrestrial lidar time series
The Earth's landscapes are shaped by processes eroding, transporting and depositing material over various timespans and spatial scales. To understand these surface activities and mitigate potential hazards they inflict (e.g., the landward movement of a shoreline), knowledge is needed on the occurrences and impact of these activities. Near-continuous terrestrial laser scanning enables the acquisition of large datasets of surface morphology, represented as three-dimensional point cloud time series. Exploiting the full potential of this large amount of data, by extracting and characterizing different types of surface activities, is challenging. In this research we use a time series of 2,942 point clouds obtained over a sandy beach in The Netherlands. We investigate automated methods to extract individual surface activities present in this dataset and cluster them into groups to characterize different types of surface activities. We show that, first extracting 2,021 spatiotemporal segments of surface activity using an object detection algorithm, and second, clustering these segments with a Self-organizing Map (SOM) in combination with hierarchical clustering, allows for the unsupervised identification and characterization of different types of surface activities present on a sandy beach. The SOM enables us to find events displaying certain type of surface activity, while it also enables the identification of subtle differences between different events belonging to one specific surface activity. Hierarchical clustering then allows us to find and characterize broader groups of surface activity, even if the same type of activity occurs at different points in space or time. Coastal EngineeringOptical and Laser Remote Sensin
Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
The metaverse has the potential to extend the physical world using augmented and virtual reality technologies allowing users to seamlessly interact within real and simulated environments using avatars and holograms. Virtual environments and immersive games (such as, Second Life, Fortnite, Roblox and VRChat) have been described as antecedents of the metaverse and offer some insight to the potential socio-economic impact of a fully functional persistent cross platform metaverse. Separating the hype and “meta…” rebranding from current reality is difficult, as “big tech” paints a picture of the transformative nature of the metaverse and how it will positively impact people in their work, leisure, and social interaction. The potential impact on the way we conduct business, interact with brands and others, and develop shared experiences is likely to be transformational as the distinct lines between physical and digital are likely to be somewhat blurred from current perceptions. However, although the technology and infrastructure does not yet exist to allow the development of new immersive virtual worlds at scale - one that our avatars could transcend across platforms, researchers are increasingly examining the transformative impact of the metaverse. Impacted sectors include marketing, education, healthcare as well as societal effects relating to social interaction factors from widespread adoption, and issues relating to trust, privacy, bias, disinformation, application of law as well as psychological aspects linked to addiction and impact on vulnerable people. This study examines these topics in detail by combining the informed narrative and multi-perspective approach from experts with varied disciplinary backgrounds on many aspects of the metaverse and its transformational impact. The paper concludes by proposing a future research agenda that is valuable for researchers, professionals and policy makers alike.Information and Communication Technolog
Search for anomaly-mediated supersymmetry breaking with the ATLAS detector based on a disappearing-track signature in pp collisions at sqrt(s) = 7TeV$
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Castaneda Hernandez;E. Castaneda-Miranda;V. Castillo Gimenez;N. F. Castro;G. Cataldi;F. Cataneo;A. Catinaccio;J. R. Catmore;A. Cattai;G. Cattani;S. Caughron;D. Cauz;P. Cavalleri;D. Cavalli;M. Cavalli-Sforza;V. Cavasinni;F. Ceradini;A. S. Cerqueira;A. Cerri;L. Cerrito;F. Cerutti;S. A. Cetin;F. Cevenini;A. Chafaq;D. Chakraborty;K. Chan;B. Chapleau;J. D. Chapman;J. W. Chapman;E. Chareyre;D. G. Charlton;V. Chavda;C. A. Chavez Barajas;S. Cheatham;S. Chekanov;S. V. Chekulaev;G. A. Chelkov;M. A. Chelstowska;C. Chen;H. Chen;S. Chen;T. Chen;X. Chen;S. Cheng;A. Cheplakov;V. F. Chepurnov;R. Cherkaoui El Moursli;V. Chernyatin;E. Cheu;S. L. Cheung;L. Chevalier;G. Chiefari;L. Chikovani;J. T. Childers;A. Chilingarov;G. Chiodini;M. V. Chizhov;G. Choudalakis;S. Chouridou;I. A. Christidi;A. Christov;D. Chromek-Burckhart;M. L. Chu;J. Chudoba;G. Ciapetti;K. Ciba;A. K. Ciftci;R. Ciftci;D. Cinca;V. Cindro;M. D. Ciobotaru;C. Ciocca;A. Ciocio;M. Cirilli;M. Citterio;M. Ciubancan;A. Clark;P. J. Clark;W. 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