Academic literature on the topic 'Scanner-laser 3D'
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Journal articles on the topic "Scanner-laser 3D"
Zeidan, Zaki M., Ashraf A. Beshr, and Ashraf G. Shehata. "Study the precision of creating 3D structure modeling form terrestrial laser scanner observations." Journal of Applied Geodesy 12, no. 4 (October 25, 2018): 303–9. http://dx.doi.org/10.1515/jag-2018-0009.
Full textGurau, Vladimir, Andy Gerhardstein, Kalvin Carruthers, and Hank Frazer. "Laser Scanner-Based Robotic Coordinate Measuring Machine." International Journal of Mechanical Engineering and Robotics Research 13, no. 1 (2024): 161–68. http://dx.doi.org/10.18178/ijmerr.13.1.161-168.
Full textRiczu, Péter, János Tamás, Gábor Nagy, Attila Nagy, Tünde Fórián, and Tamás Jancsó. "Horticulture applicability of 3D laser scanner." Acta Agraria Debreceniensis, no. 46 (May 16, 2012): 75–78. http://dx.doi.org/10.34101/actaagrar/46/2412.
Full textChen, Kai, Kai Zhan, Xiaocong Yang, and Da Zhang. "Accuracy Improvement Method of a 3D Laser Scanner Based on the D-H Model." Shock and Vibration 2021 (May 25, 2021): 1–9. http://dx.doi.org/10.1155/2021/9965904.
Full textJang, Arum, Young K. Ju, and Min Jae Park. "Structural Stability Evaluation of Existing Buildings by Reverse Engineering with 3D Laser Scanner." Remote Sensing 14, no. 10 (May 11, 2022): 2325. http://dx.doi.org/10.3390/rs14102325.
Full textPalomer, Albert, Pere Ridao, Dina Youakim, David Ribas, Josep Forest, and Yvan Petillot. "3D Laser Scanner for Underwater Manipulation." Sensors 18, no. 4 (April 4, 2018): 1086. http://dx.doi.org/10.3390/s18041086.
Full textRioux, M., and T. Bird. "White laser, synced scan (3D scanner)." IEEE Computer Graphics and Applications 13, no. 3 (May 1993): 15–17. http://dx.doi.org/10.1109/38.210485.
Full textGao, X., M. Li, L. Xing, and Y. Liu. "JOINT CALIBRATION OF 3D LASER SCANNER AND DIGITAL CAMERA BASED ON DLT ALGORITHM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 377–80. http://dx.doi.org/10.5194/isprs-archives-xlii-3-377-2018.
Full textSyed Abdullah, Sharifah Lailaton Khadijah, and Siti Kamisah Mohd Yusof. "Generating a 3D Model Parking Lot by using Terrestrial Laser Scanner." Jurnal Kejuruteraan 34, no. 3 (May 30, 2022): 411–19. http://dx.doi.org/10.17576/jkukm-2022-34(3)-08.
Full textMezian, c., Bruno Vallet, Bahman Soheilian, and Nicolas Paparoditis. "UNCERTAINTY PROPAGATION FOR TERRESTRIAL MOBILE LASER SCANNER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 331–35. http://dx.doi.org/10.5194/isprs-archives-xli-b3-331-2016.
Full textDissertations / Theses on the topic "Scanner-laser 3D"
Liu, Junjie. "3D laser scanner development and analysis." Thesis, Aberystwyth University, 2013. http://hdl.handle.net/2160/b3a1beca-3d92-48bc-945e-2e50b3e7755a.
Full textPreuksakarn, Chakkrit. "Reconstructing plant architecture from 3D laser scanner data." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20116/document.
Full textIn the last decade, very realistic rendering of plant architectures have been produced in computer graphics applications. However, in the context of biology and agronomy, acquisition of accurate models of real plants is still a tedious task and a major bottleneck for the construction of quantitative models of plant development. Recently, 3D laser scanners made it possible to acquire 3D images on which each pixel has an associate depth corresponding to the distance between the scanner and the pinpointed surface of the object. Standard geometrical reconstructions fail on plants structures as they usually contain a complex set of discontinuous or branching surfaces distributed in space with varying orientations. In this thesis, we present a method for reconstructing virtual models of plants from laser scanning of real-world vegetation. Measuring plants with laser scanners produces data with different levels of precision. Points set are usually dense on the surface of the main branches, but only sparsely cover thin branches. The core of our method is to iteratively create the skeletal structure of the plant according to local density of point set. This is achieved thanks to a method that locally adapts to the levels of precision of the data by combining a contraction phase and a local point tracking algorithm. In addition, we present a quantitative evaluation procedure to compare our reconstructions against expertised structures of real plants. For this, we first explore the use of an edit distance between tree graphs. Alternatively, we formalize the comparison as an assignment problem to find the best matching between the two structures and quantify their differences
Wachten, Christian. "Entwicklung eines Lasertrackersystems mit Galvanometerscanner zur 3D-Positionsbestimmung." Tönning Lübeck Marburg Der Andere Verl, 2009. http://d-nb.info/994323778/04.
Full textAzim, Asma. "3D Perception of Outdoor and Dynamic Environment using Laser Scanner." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM070/document.
Full textWith an anticipation to make driving experience safer and more convenient, over the decades, researchers have tried to develop intelligent systems for modern vehicles. The intended systems can either drive automatically or monitor a human driver and assist him in navigation by warning in case of a developing dangerous situation. Contrary to the human drivers, these systems are not constrained by many physical and psychological limitations and therefore prove more robust in extreme conditions. A key component of an intelligent vehicle system is the reliable perception of the environment. Laser range finders have been popular sensors which are widely used in this context. The classical 2D laser scanners have some limitations which are often compensated by the addition of other complementary sensors including cameras and radars. The recent advent of new sensors, such as 3D laser scanners which perceive the environment at a high spatial resolution, has proven to be an interesting addition to the arena. Although there are well-known methods for perception using 2D laser scanners, approaches using a 3D range scanner are relatively rare in literature. Most of those which exist either address the problem partially or augment the system with many other sensors. Surprisingly, many of those rely on reducing the dimensionality of the problem by projecting 3D data to 2D and using the well-established methods for 2D perception. In contrast to these approaches, this work addresses the problem of vehicle perception using a single 3D laser scanner. First contribution of this research is made by the extension of a generic 3D mapping framework based on an optimized occupancy grid representation to solve the problem of simultaneous localization and mapping (SLAM). Using the 3D occupancy grid, we introduce a variance-based elevation map for the segmentation of range measurements corresponding to the ground. To correct the vehicle location from odometry, we use a grid-based incremental scan matching method. The resulting SLAM framework forms a basis for rest of the contributions which constitute the major achievement of this work. After obtaining a good vehicle localization and a reliable map with ground segmentation, we focus on the detection and tracking of moving objects (DATMO). The second contribution of this thesis is the method for discriminating between the dynamic objects and the static environment. The presented approach uses motion-based detection and density-based clustering for segmenting the moving objects from 3D occupancy grid. It does not use object specific models but enables detecting arbitrary traffic participants. Third contribution is an innovative method for layered classification of the detected objects based on supervised learning technique which makes it easier to estimate their position with time. Final contribution is a method for tracking the detected objects by using Viterbi algorithm to associate the new observations with the existing objects in the environment. The proposed framework is verified with the datasets acquired from a laser scanner mounted on top of a vehicle moving in different environments including urban, highway and pedestrian-zone scenarios. The promising results thus obtained show the applicability of the proposed system for simultaneous localization and mapping with detection, classification and tracking of moving objects in dynamic outdoor environments using a single 3D laser scanner
Gonçales, Rodrigo. "Dispositivo de varredura laser 3D terrestre e suas aplicações na engenharia, com ênfase em túneis." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/3/3138/tde-10082007-173531/.
Full textNew technologies are constantly being developed in order to collect information of surfaces or solids for diverse purposes. Some classic methods such as topography and terrestrial photogrammetry have had a great evolution in the past. For example, all the processes of the terrestrial photogrammetry are made in digital way and the Total Stations have automated the measurements of angles and distances. This technical evolution made the surveying faster and accurate, increasing the productivity. However this evolution does not stop for there; in other words, the last technology in the area of topography is the surveying with the system known as Laser Scanner 3D. The Laser Scanner technology 3D has a lot of applications such as: tunnel, as-built, mining (mainly in the underground); archaeology (for restore monuments), refineries, industrial installations, etc., characterized by the great complexity of the involved elements. This work presents concepts involved in all the processes, since from data collection to the final product. It develops a methodology of use that can be applied in several areas, with emphasis in tunnels surveying area and presents some tests to quantization the accuracy.
Cacciari, Pedro Pazzoto. "Estudo de um túnel em maciço rochoso fraturado por investigação geológico-geotécnica e análises pelo método dos elementos distintos." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3145/tde-26082015-153054/.
Full textThe geomechanical behaviour of rock tunnels is strongly influenced by geological structures in the rock mass. Rock discontinuities are geometrically characterized by parameters that describes their orientations, frequency and lengths. In most cases, these parameters are determined in field inspections, using geological compass and measuring tapes. However, timeframes and access limitation hinder this procedure, making it impossible to obtain large amount of data that allow complex statistical analysis. To overcome these difficulties, here the discontinuity mapping was performed using images of the Monte Seco tunnel, obtained by 3D terrestrial laser scanning. In this case, the orientation, position and trace length of each discontinuity was determined with precision, allowing the verification of the fracture intensity distribution in different parts of the tunnel. Using these parts (differentiated by its fracture intensities), statistical analyses were performed, using sampling windows and scanlines, in order to determine the orientation mean trace length and spacing of discontinuity sets. Once the geometrical parameters of discontinuity sets were determined, a probabilistic model of rigid blocks was generated, using the 3DEC software. Thus, the mechanical parameters of discontinuity sets were estimated by empirical correlations (performed using descriptions of the rock mass obtained during geological inspections in the tunnel), and some laboratory and field tests. The analyses with this model were performed to verify the instability of blocks (block falls), and compared with actual cross sections of the tunnel. The results indicate that different failure criteria must be used for different discontinuity types (fractures and foliation), and revealed the importance of consistent estimated of geometrical parameters of discontinuity sets.
Střižík, Jakub. "Vizualizace dat z 3D laserového skeneru." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220141.
Full textSchilling, Anita. "Automatic Retrieval of Skeletal Structures of Trees from Terrestrial Laser Scanner Data." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-155698.
Full textDie Erforschung des ÖkosystemsWald spielt gerade heutzutage im Hinblick auf den nachhaltigen Umgang mit nachwachsenden Rohstoffen und den Klimawandel eine große Rolle. Insbesondere die exakte Beschreibung der dreidimensionalen Struktur eines Baumes ist wichtig für die Forstwissenschaften und Bioklimatologie, aber auch im Rahmen kommerzieller Anwendungen. Die konventionellen Methoden um geometrische Pflanzenmerkmale zu messen sind arbeitsintensiv und zeitaufwändig. Für eine genaue Analyse müssen Bäume gefällt werden, was oft unerwünscht ist. Hierbei bietet sich das Terrestrische Laserscanning (TLS) als besonders attraktives Werkzeug aufgrund seines kontaktlosen Messprinzips an. Die Objektgeometrie wird als 3D-Punktwolke wiedergegeben. Basierend darauf ist das Ziel der Arbeit die automatische Bestimmung der räumlichen Baumstruktur aus TLS-Daten. Der Fokus liegt dabei auf Waldszenen mit vergleichsweise hoher Bestandesdichte und mit zahlreichen daraus resultierenden Verdeckungen. Die Auswertung dieser TLS-Daten, die einen unterschiedlichen Grad an Detailreichtum aufweisen, stellt eine große Herausforderung dar. Zwei vollautomatische Methoden zur Generierung von Skelettstrukturen von gescannten Bäumen, welche komplementäre Eigenschaften besitzen, werden vorgestellt. Bei der ersten Methode wird das Gesamtskelett eines Baumes aus 3D-Daten von registrierten Scans bestimmt. Die Aststruktur wird von einer Voxelraum-Repräsentation abgeleitet indem Pfade von Astspitzen zum Stamm gesucht werden. Der Stamm wird im Voraus aus den 3D-Punkten rekonstruiert. Das Baumskelett wird als 3D-Liniengraph erzeugt. Für jeden gemessenen Punkt stellt ein Scan neben 3D-Koordinaten und Distanzwerten auch 2D-Indizes zur Verfügung, die sich aus dem Intensitätsbild ergeben. Bei der zweiten Methode, die auf Einzelscans arbeitet, wird dies ausgenutzt. Außerdem wird ein neuartiges Konzept zum Management von TLS-Daten beschrieben, welches die Forschungsarbeit erleichtert hat. Zunächst wird das Tiefenbild in Komponenten aufgeteilt. Es wird eine Prozedur zur Bestimmung von Komponentenkonturen vorgestellt, die in der Lage ist innere Tiefendiskontinuitäten zu verfolgen. Von der Konturinformation wird ein 2D-Skelett generiert, welches benutzt wird um die Komponente in Teilkomponenten zu zerlegen. Von der 3D-Punktmenge, die mit einer Teilkomponente assoziiert ist, wird eine Principal Curve berechnet. Die Skelettstruktur einer Komponente im Tiefenbild wird als Menge von Polylinien zusammengefasst. Die objektive Evaluation der Resultate stellt weiterhin ein ungelöstes Problem dar, weil die Aufgabe selbst nicht klar erfassbar ist: Es existiert keine eindeutige Definition davon was das wahre Skelett in Bezug auf eine gegebene Punktmenge sein sollte. Die Korrektheit der Methoden kann daher nicht quantitativ beschrieben werden. Aus diesem Grund, können die Ergebnisse nur visuell beurteiltwerden. Weiterhinwerden die Charakteristiken beider Methoden eingehend diskutiert. Es werden Experimentresultate beider Methoden vorgestellt. Die erste Methode bestimmt effizient das Skelett eines Baumes, welches die Aststruktur approximiert. Der Detaillierungsgrad wird hauptsächlich durch den Voxelraum bestimmt, weshalb kleinere Äste nicht angemessen reproduziert werden. Die zweite Methode rekonstruiert Teilskelette eines Baums mit hoher Detailtreue. Die Methode reagiert sensibel auf Rauschen in der Kontur, dennoch sind die Ergebnisse vielversprechend. Es gibt eine Vielzahl von Möglichkeiten die Robustheit der Methode zu verbessern. Die Kombination der Stärken von beiden präsentierten Methoden sollte weiter untersucht werden und kann zu einem robusteren Ansatz führen um vollständige Baumskelette automatisch aus TLS-Daten zu generieren
Janoušek, Pavel. "Modernizace 3D měřicího přístroje." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2012. http://www.nusl.cz/ntk/nusl-230151.
Full textRahel, Rahel. "Mesure de champs de déplacements 3D à l'aide d'un scanner laser couplé à une caméra." Dijon, 2009. http://www.theses.fr/2009DIJOS033.
Full textBooks on the topic "Scanner-laser 3D"
Elberink, Sander Oude. Acquisition of 3D topography: Automated 3D road and building reconstruction using airborne laser scanner data and topographic maps. Delft: NCG, Netherlands Geodetic Commission, 2010.
Find full textGuyer, J. Introduction to Terrestrial 3D Laser Scanner Topographic Survey Procedures. Independently Published, 2018.
Find full textBook chapters on the topic "Scanner-laser 3D"
Héno, Raphaële, and Laure Chandelier. "3D Digitization by Laser Scanner." In 3D Modeling of Buildings, 85–124. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118648889.ch3.
Full textMüller, A., M. Schubert, and L. Verges. "Laser-3D-Scanner für die Endoskopie." In Laser in der Medizin Laser in Medicine, 607. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-60306-8_124.
Full textLlamazares, Á., E. J. Molinos, M. Ocaña, L. M. Bergasa, N. Hernández, and F. Herranz. "3D Map Building Using a 2D Laser Scanner." In Computer Aided Systems Theory – EUROCAST 2011, 412–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27579-1_53.
Full textDurante, Francesco, and Pierluigi Beomonte Zobel. "Development of a Time of Flight Laser Scanner 3D." In Advances in Intelligent Systems and Computing, 538–45. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65960-2_66.
Full textBarba, Salvatore, Francesco Villecco, and Alessandro Naddeo. "“Ultima Dea”: A Laser Scanner Application for 3D Modelling." In Advances in Intelligent Systems and Computing, 559–69. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95588-9_46.
Full textZhang, Wang, Deshan Yang, Ying Li, and Wenhai Xu. "Portable 3D Laser Scanner for Volume Measurement of Coal Pile." In Lecture Notes in Electrical Engineering, 340–47. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6508-9_41.
Full textAdán, Antonio, David de la Rubia, and Andrés S. Vázquez. "Obtaining and Monitoring Warehouse 3D Models with Laser Scanner Data." In ROBOT 2017: Third Iberian Robotics Conference, 227–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70836-2_19.
Full textElberink, Sander Oude. "Re-using laser scanner data in applications for 3D topography." In Lecture Notes in Geoinformation and Cartography, 87–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-72135-2_5.
Full textLamovsky, Denis, and Aless Lasaruk. "Calibration and Reconstruction Algorithms for a Handheld 3D Laser Scanner." In Advanced Concepts for Intelligent Vision Systems, 635–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23687-7_57.
Full textTrinh, Nhon H., Jonathan Lester, Braden C. Fleming, Glenn Tung, and Benjamin B. Kimia. "Accurate Measurement of Cartilage Morphology Using a 3D Laser Scanner." In Computer Vision Approaches to Medical Image Analysis, 37–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11889762_4.
Full textConference papers on the topic "Scanner-laser 3D"
Mahjoubfar, A., K. Goda, C. Wang, A. Fard, J. Adam, D. R. Gossett, A. Ayazi, et al. "3D ultrafast laser scanner." In SPIE LASE, edited by Alexander Heisterkamp, Peter R. Herman, Michel Meunier, and Stefan Nolte. SPIE, 2013. http://dx.doi.org/10.1117/12.2003135.
Full textThanusutiyabhorn, Pimrapat, Pizzanu Kanongchaiyos, and Waleed S. Mohammed. "Image-based 3D laser scanner." In 2011 8th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2011). IEEE, 2011. http://dx.doi.org/10.1109/ecticon.2011.5948005.
Full textKocmanova, Petra, Ludek Zalud, and Adam Chromy. "3D proximity laser scanner calibration." In 2013 18th International Conference on Methods & Models in Automation & Robotics (MMAR). IEEE, 2013. http://dx.doi.org/10.1109/mmar.2013.6670005.
Full textYoshida, Tomoaki, Kiyoshi Irie, Eiji Koyanagi, and Masahiro Tomono. "3D laser scanner with gazing ability." In 2011 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2011. http://dx.doi.org/10.1109/icra.2011.5980385.
Full textXianfang Sun, Paul L. Rosin, Ralph R. Martin, and Frank C. Langbein. "Noise in 3D laser range scanner data." In 2008 IEEE International Conference on Shape Modeling and Applications (SMI). IEEE, 2008. http://dx.doi.org/10.1109/smi.2008.4547945.
Full textNishida, Y., S. Yasukawa, and K. Ishii. "Underwater 3D Scanner using RGB Laser pattern." In 2021 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf49454.2021.9382643.
Full textGeusen, Jr., Mark, Willem D. van Amstel, Stefan M. B. Baumer, and Jef L. Horijon. "Design of a compact 3D laser scanner." In Optical Systems Design and Production, edited by Fritz Merkle. SPIE, 1999. http://dx.doi.org/10.1117/12.360015.
Full textVitor Cantarella, João Paulo Monticeli, Pedro Pazzoto Cacciari, and Marcos Massao Futai. "JRC estimation with 3D laser scanner images." In VII Simpósio Brasileiro de Mecânica das Rochas. São Paulo, SP, Brasil: Associação Brasileira de Mecânica dos Solos e Engenharia Geotécnica - ABMS, 2016. http://dx.doi.org/10.20906/cps/sbmr-02-0024.
Full textLi, Bai-yun, Chun-xia Zhao, and Yi Zheng. "3D Scene Reconstruction Method Based on Laser Scanner." In 2009 1st International Conference on Information Science and Engineering (ICISE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icise.2009.4.
Full textKurisaki, Naoko, Wentao Che, and Tatsuhide Nakane. "Applications of 3D measurement with ground laser scanner." In Photonics West 2001 - Electronic Imaging, edited by Sabry F. El-Hakim and Armin Gruen. SPIE, 2000. http://dx.doi.org/10.1117/12.410865.
Full textReports on the topic "Scanner-laser 3D"
Augustoni, Arnold L. 3rd Tech DeltaSphere-3000 Laser 3D Scene Digitizer infrared laser scanner hazard analysis. Office of Scientific and Technical Information (OSTI), February 2005. http://dx.doi.org/10.2172/920773.
Full textDesa, Hazry, Muhammad Azizi Azizan, Nur Zakirah Rabiha Md. Rejab, and Mohd Shafiq Ismail. CONSERVATION WORKS ON HERITAGE BUILDING: GENERATING AS BUILT DRAWING BY UAV APPLICATION AND 3D LASER SCANNER FOR FACILITIES MAINTENANCE. Penerbit Universiti Malaysia Perlis, 2023. http://dx.doi.org/10.58915/techrpt2023.002.
Full textKrishnamurthy and Gao. PR-328-073511-R01 Detection and Discrimination of Mechanical Damage using Improved ILI Tools. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 2013. http://dx.doi.org/10.55274/r0010809.
Full textJackson, Sam S., and Michael J. Bishop. Use of a High-Resolution 3D Laser Scanner for Minefield Surface Modeling and Terrain Characterization: Temperate Region. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada438210.
Full textJackson, Sam S., and Michael J. Bishop. Use of a High-Resolution 3D Laser Scanner for Minefield Surface Modeling and Terrain Characterization: Temperature Region. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada443802.
Full textCoastal Lidar And Radar Imaging System (CLARIS) mobile terrestrial lidar survey along the Outer Banks, North Carolina in Currituck and Dare counties. Coastal and Hydraulics Laboratory (U.S.), January 2020. http://dx.doi.org/10.21079/11681/39419.
Full textCoastal Lidar And Radar Imaging System (CLARIS) mobile terrestrial lidar survey along the Outer Banks, North Carolina in Currituck and Dare counties. Coastal and Hydraulics Laboratory (U.S.), January 2020. http://dx.doi.org/10.21079/11681/39419.
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