Relevant bibliographies by topics / Réflectance lidar de surface

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Réflectance lidar de surface'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Réflectance lidar de surface"

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Rudant, Jean-Paul, and Pierre-Louis Frison. "Lettre : Existe-t-il des relations formelles entre coefficients de diffusion radar et facteurs de réflectance en optique ?" Revue Française de Photogrammétrie et de Télédétection, no. 219-220 (January 17, 2020): 29–31. http://dx.doi.org/10.52638/rfpt.2019.461.

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Cette note tente de répondre à de fréquentes questions touchant à la comparaison optique et radar, par exemple : quelles sont les relations formelles existant entre coefficients de diffusion radar et facteurs de réflectance en optique ? Comment les images reflètent elles les coefficients optiques ou radar destinés à caractériser la surface ?
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Lafrance, Bruno, Xavier Lenot, Caroline Ruffel, Patrick Cao, and Thierry Rabaute. "Outils de prétraitements des images optiques Kalideos." Revue Française de Photogrammétrie et de Télédétection, no. 197 (April 21, 2014): 10–16. http://dx.doi.org/10.52638/rfpt.2012.78.

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La communauté scientifique a besoin de disposer de séries temporelles d'observations récurrentes, couvrant des sites d'intérêt pour le suivi de l'évolution des surfaces terrestres (études agronomiques par assimilation de données, suivi de traits de côte, glissements de terrain, surveillance des volcans, cartographie littorale, etc.). L'analyse de ces séries temporelles demande à avoir des images superposables entre elles qui renseignent sur la réflectance des sites (grandeur physique indépendante du capteur).Dans l'objectif de rendre accessibles de telles données physiques et de garantir une h
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LIN, C. S. "Ocean surface profiling lidar." International Journal of Remote Sensing 17, no. 13 (1996): 2667–80. http://dx.doi.org/10.1080/01431169608949098.

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CHAMP, M., and P. COLONNA. "Importance de l’endommagement de l’amidon dans les aliments pour animaux." INRAE Productions Animales 6, no. 3 (1993): 185–98. http://dx.doi.org/10.20870/productions-animales.1993.6.3.4199.

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Les principales modifications de l’état de l’amidon, qui se produisent au cours des étapes de transformation et de fabrication des aliments pour animaux, sont l’augmentation de surface spécifique, une diminution de la cristallinité et une dépolymérisation de l’amylose et de l’amylopectine. Les différentes méthodes in vitro qui permettent d’étudier les facteurs influençant les cinétiques d’hydrolyse de l’amidon sont présentées. La microscopie permet des observations qualitatives. Les déterminations quantitatives sont fondées sur la susceptibilité aux amylases, les solubilités en milieux aqueux
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Mandlburger, Gottfried, and Boris Jutzi. "On the Feasibility of Water Surface Mapping with Single Photon LiDAR." ISPRS International Journal of Geo-Information 8, no. 4 (2019): 188. http://dx.doi.org/10.3390/ijgi8040188.

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Single photon sensitive airborne Light Detection And Ranging (LiDAR) enables a higher area performance at the price of an increased outlier rate and a lower ranging accuracy compared to conventional Multi-Photon LiDAR. Single Photon LiDAR, in particular, uses green laser light potentially capable of penetrating clear shallow water. The technology is designed for large-area topographic mapping, which also includes the water surface. While the penetration capabilities of green lasers generally lead to underestimation of the water level heights, we specifically focus on the questions of whether S
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Yang, Song, Qian Sun, and Yongchao Zheng. "Simulation Effects of Surface Geometry and Water Optical Properties on Hydrographic Lidar Returns." EPJ Web of Conferences 237 (2020): 08020. http://dx.doi.org/10.1051/epjconf/202023708020.

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. Water LiDAR model was applied to simulate the returned waveforms of hydrographic LiDAR considering the effects of surface geometry and water optical properties. The signal to noise ratio(SNR) of bottom returned peak was considered as a criterion for performance of hydrographic LiDAR. The behavior of LiDAR was sensitive to water optical properties and it was insensitive to water surface roughness.
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Belov, M. L., A. M. Belov, V. A. Gorodnichev, and S. V. Alkov. "Monopulse lidar Earth surface sounding method." IOP Conference Series: Materials Science and Engineering 537 (June 17, 2019): 022047. http://dx.doi.org/10.1088/1757-899x/537/2/022047.

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Sedláček, Jozef, Ondřej Šesták, and Miroslava Sliacka. "Comparison of Digital Elevation Models by Visibility Analysis in Landscape." Acta Horticulturae et Regiotecturae 19, no. 2 (2016): 28–31. http://dx.doi.org/10.1515/ahr-2016-0007.

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Abstract The paper investigates suitability of digital surface model for visibility analysis in GIS. In experiment there were analysed viewsheds from 14 observer points calculated on digital surface model, digital terrain model and its comparison to field survey. Data sources for the investigated models were LiDAR digital terrain model and LiDAR digital surface model with vegetation distributed by the Czech Administration for Land Surveying and Cadastre. The overlay method was used for comparing accuracy of models and the reference model was LiDAR digital surface model. Average equalities in c
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Webster, Tim, Candace MacDonald, Kevin McGuigan, Nathan Crowell, Jean-Sebastien Lauzon-Guay, and Kate Collins. "Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada." Botanica Marina 63, no. 1 (2020): 43–59. http://dx.doi.org/10.1515/bot-2018-0080.

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AbstractThe ability to map and monitor the macroalgal coastal resource is important to both the industry and the regulator. This study evaluates topo-bathymetric lidar (light detection and ranging) as a tool for estimating the surface area, height and biomass of Ascophyllum nodosum, an anchored and vertically suspended (floating) macroalga, and compares the surface area derived from lidar and WorldView-2 satellite imagery. Pixel-based Maximum Likelihood classification of low tide satellite data produced 2-dimensional maps of intertidal macroalgae with overall accuracy greater than 80%. Low tid
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Taheri Andani, Masood, Abdullah Mohammed, Ashish Jain, and Mehdi Ahmadian. "Application of LIDAR technology for rail surface monitoring and quality indexing." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 5 (2017): 1398–406. http://dx.doi.org/10.1177/0954409717727200.

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This paper investigates the application of Doppler Light Detection and Ranging (LIDAR) sensors for the assessment of the top of rail lubricity condition and layer material. Different top of rail conditions are distinguished by the system using a new pair of rail surface indices defined based on LIDAR measurements. These indices provide quantitative representations of the top of rail condition due to the fact that Doppler frequency range and spectral magnitude of a backscattered LIDAR beam are functions of the rail surface figure as well as the light absorption properties of the surface materia
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Dissertations / Theses on the topic "Réflectance lidar de surface"

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Zabukovec, Antonin. "Apport des mesures de la plateforme CALIPSO pour l’étude des sources et des propriétés optiques des aérosols en Sibérie." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS393.

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Les connaissances sur la distribution et les propriétés physico-chimiques des particules aérosols dans la troposphère ont été identifiées par le Groupe d’experts Intergouvernemental sur l’Évolution du Climat (GIEC) comme la principale source d’incertitude dans l’étude de l’évolution du climat. Une caractérisation des types, des propriétés optiques et de la distribution verticale des aérosols à l’échelle régionale est nécessaire pour réduire cette source d’incertitude et certaines zones comme la Sibérie sont encore mal documentées. Les concentrations en aérosol de la Sibérie dépendent de source
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Morel, Jules. "Surface reconstruction based on forest terrestrial LiDAR data." Thesis, Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0039/document.

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Au cours des dernières années, la capacité de la technologie LiDAR à capturer des informations détaillées sur la structure des forêts a attiré une attention croissante de la part de la communauté des écologues et des forestiers. Le LiDAR terrestre, notamment, apparaît comme un outil prometteur pour recueillir les caractéristiques géométriques des arbres à une précision millimétrique.Cette thèse étudie la reconstruction de surface à partir de nuages de points épars et non structurés, capturés en environnement forestier par un LiDAR terrestre. Nous proposons une suite d’algorithmes dédiés à la r
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Venkata, Srikanth, and John Reagan. "Aerosol Retrievals from CALIPSO Lidar Ocean Surface Returns." MDPI AG, 2016. http://hdl.handle.net/10150/622759.

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This paper describes approaches to retrieve important aerosol results from the strong lidar return signals that are received by the space-borne CALIPSO lidar system after reflecting off-ocean surfaces. Relations, from which the theoretically expected values of area under ocean surface returns can be computed, are presented. A detailed description of the lidar system response to the ocean surface returns and the processes of sampling and averaging of lidar return signals are provided. An effective technique that reconstructs the lidar response to surface returnsstarting from down-linked samples
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Sarma, Vaibhav Yuan Xiaohui. "Urban surface characterization using LiDAR and aerial imagery." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12196.

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Sarma, Vaibhav. "Urban surface characterization using LiDAR and aerial imagery." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12196/.

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Many calamities in history like hurricanes, tornado and flooding are proof to the large scale impact they cause to the life and economy. Computer simulation and GIS helps in modeling a real world scenario, which assists in evacuation planning, damage assessment, assistance and reconstruction. For achieving computer simulation and modeling there is a need for accurate classification of ground objects. One of the most significant aspects of this research is that it achieves improved classification for regions within which light detection and ranging (LiDAR) has low spatial resolution. This thesi
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Le, Bras Aurélie. "Etude de l'état de surface des astéroïdes par spectroscopie infrarouge en réflectance." Paris 7, 2001. http://www.theses.fr/2001PA077139.

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Awadallah, Mahmoud Sobhy Tawfeek. "Image Analysis Techniques for LiDAR Point Cloud Segmentation and Surface Estimation." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73055.

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Light Detection And Ranging (LiDAR), as well as many other applications and sensors, involve segmenting sparse sets of points (point clouds) for which point density is the only discriminating feature. The segmentation of these point clouds is challenging for several reasons, including the fact that the points are not associated with a regular grid. Moreover, the presence of noise, particularly impulsive noise with varying density, can make it difficult to obtain a good segmentation using traditional techniques, including the algorithms that had been developed to process LiDAR data. This disser
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Flanagin, Maik. "The Hydraulic Spline: Comparisons of Existing Surface Modeling Techniques and Development of a Spline-Based Approach for Hydrographic and Topographic Surface Modeling." ScholarWorks@UNO, 2007. http://scholarworks.uno.edu/td/613.

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Creation of accurate and coherent surface models is vital to the effective planning and construction of flood control and hurricane protection projects. Typically, topographic surface models are synthesized from Delaunay triangulations or interpolated raster grids. Although these techniques are adequate in most general situations, they do not effectively address the specific case where topographic data is available only as cross-section and profile centerline data, such as the elevation sampling produced by traditional hydrographic surveys. The hydraulic spline algorithm was developed to
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Jack, Landy. "Characterization of sea ice surface topography using Light Detection and Ranging (LiDAR)." Wiley, 2014. http://hdl.handle.net/1993/31170.

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Where once the Arctic basin held predominantly old, thick perennial sea ice, it is now increasingly occupied by young, thin seasonal ice. The sea ice surface topography, which affects and is affected by many of the physical processes operating at the interface between ocean, sea ice and atmosphere, is closely related to the age and type of sea ice cover. In this thesis, new methods are presented for measuring and understanding sea ice topography using Light Detection and Ranging (LiDAR) technology. A new technique is presented for parameterizing the micro-scale roughness of sea ice using terr
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Mutlu, Muge. "Mapping surface fuels using LIDAR and multispectral data fusion for fire behavior modeling." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1118.

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Books on the topic "Réflectance lidar de surface"

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Society of Light and Lighting and National Physical Laboratory (Great Britain), eds. Lighting guide 11: Surface reflectance and colour : its specification and measurement for designers. The Society of Light and Lighting, 2001.

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Persaud, Arlene S. Design beyond the visible spectrum: Leveraging scientific data to generate surface models for hyper-realistic visualization. 2010.

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Hapke, Bruce. Theory of Reflectance and Emittance Spectroscopy. Cambridge University Press, 2009.

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Hapke, Bruce. Theory of Reflectance and Emittance Spectroscopy. Cambridge University Press, 2012.

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Hapke, Bruce. Theory of Reflectance and Emittance Spectroscopy. Cambridge University Press, 2012.

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Hapke, Bruce. Theory of Reflectance and Emittance Spectroscopy. Cambridge University Press, 2011.

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Hapke, Bruce. Theory of Reflectance and Emittance Spectroscopy. Cambridge University Press, 2012.

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Book chapters on the topic "Réflectance lidar de surface"

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Reagan, J. A., H. Liu, and T. W. Cooley. "LITE Surface Returns: Assessment and Applications." In Advances in Atmospheric Remote Sensing with Lidar. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60612-0_44.

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Li, Yongguo, Yuanrong Wang, Jia Xie, and Kun Zhang. "Unmanned Surface Vehicle Target Detection Based on LiDAR." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1095-9_11.

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Vu, Ngoc Quang, and Hoa Pham Thi Thanh. "Mobile Lidar for Road Surface Monitoring: A Case Study of an Integrated AU20 Lidar." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0399-9_53.

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Inoue, Masato, Yosuke Kawasaki, Takuma Suzuki, Yuta Washimi, Tsutomu Tanimoto, and Masaki Takahashi. "Point Cloud Interpolation by RGB Image to Estimate Road Surface Profile for Preview Suspension Control." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_95.

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AbstractThe growing prevalence of autonomous driving is expected to shift passengers’ attention from driving, increasing the demand for enhanced ride comfort. Studies addressing ride comfort have prominently explored active suspension control with recent research on preview suspension control using on-board sensors. The proposed systems often include LiDAR deployment at the front for high-precision road surface profiles. However, these systems often involve costly sensors such as LiDAR, making it impractical for on-board installation. Nonetheless, in recent autonomous vehicles, LiDAR tend to b
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Maanpää, Jyri, Julius Pesonen, Heikki Hyyti, et al. "Dense Road Surface Grip Map Prediction from Multimodal Image Data." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78447-7_26.

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AbstractSlippery road weather conditions are prevalent in many regions and cause a regular risk for traffic. Still, there has been less research on how autonomous vehicles could detect slippery driving conditions on the road to drive safely. In this work, we propose a method to predict a dense grip map from the area in front of the car, based on postprocessed multimodal sensor data. We trained a convolutional neural network to predict pixelwise grip values from fused RGB camera, thermal camera, and LiDAR reflectance images, based on weakly supervised ground truth from an optical road weather s
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Al-Durgham, M., G. Fotopoulos, and C. Glennie. "On the Accuracy of LiDAR Derived Digital Surface Models." In Gravity, Geoid and Earth Observation. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10634-7_90.

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Liu, Maohua, Xiubo Sun, Yue Shao, and Yingchun You. "Surface Features Classification of Airborne Lidar Data Based on TerraScan." In Geo-informatics in Sustainable Ecosystem and Society. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7025-0_19.

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Hu, Hui, Tomas M. Fernandez-Steeger, Mei Dong, and Rafig Azzam. "Deformation Monitoring and Recognition of Surface Mine Slope Using LiDAR." In Engineering Geology for Society and Territory - Volume 2. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09057-3_73.

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Ma, Jianfei, Ruoyang Song, Tao Han, Arturo Sanchez-Azofeifa, and Anup Basu. "Poisson Surface Reconstruction from LIDAR for Buttress Root Volume Estimation." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54407-2_39.

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Abed, Fanar M. "Correlation Between Surface Modeling and Pulse Width of FWF-Lidar." In Advances in Remote Sensing and Geo Informatics Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01440-7_34.

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Conference papers on the topic "Réflectance lidar de surface"

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Shiina, Tatsuo, Yasuyuki Kawakami, Takumi Ikeda, Kunihiko Katano, and Yuta Yamaguchi. "Surface atmosphere observation with 265nm LED mini-lidar." In Remote Sensing of Clouds and the Atmosphere XXIX, edited by Evgueni I. Kassianov and Simone Lolli. SPIE, 2024. http://dx.doi.org/10.1117/12.3031680.

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Luo, Weihan, Anagh Malik, and David B. Lindell. "Transientangelo: Few-Viewpoint Surface Reconstruction Using Single-Photon Lidar." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00845.

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Yusofsani, Seyedmohammad, and Yuzuru Takashima. "Bulk and surface acoustic waves for display and lidar applications." In ODS 2024: Industrial Optical Devices and Systems, edited by Ryuichi Katayama and Yuzuru Takashima. SPIE, 2024. http://dx.doi.org/10.1117/12.3028862.

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Lin, Bing Cheng, Ming Chen, Szi Yan Chuah, and Wan Chun Huang. "High performance and reliability of 940nm multijunction VCSEL arrays for 3D sensing and LiDAR applications." In Vertical-Cavity Surface-Emitting Lasers XXIX, edited by Kent D. Choquette and Luke A. Graham. SPIE, 2025. https://doi.org/10.1117/12.3042485.

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Blanton, Hunter, Sean Grate, and Nathan Jacobs. "Surface Modeling for Airborne Lidar." In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2020. http://dx.doi.org/10.1109/igarss39084.2020.9323522.

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Herper, Markus, Stephan Gronenborn, Xi Gu, Johanna Kolb, Michael Miller, and Holger Moench. "VECSEL for 3D LiDAR applications." In Vertical External Cavity Surface Emitting Lasers (VECSELs) IX, edited by Ursula Keller. SPIE, 2019. http://dx.doi.org/10.1117/12.2507740.

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Church, Philip M., Justin Matheson, Brett Owens, and Christopher Grebe. "Aerial and surface security applications using lidar." In Laser Radar Technology and Applications XXIII, edited by Monte D. Turner and Gary W. Kamerman. SPIE, 2018. http://dx.doi.org/10.1117/12.2304348.

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Jain, Sohan L., B. C. Arya, Sachin D. Ghude, Arun K. Arora, and Randhir K. Sinha. "Surface ozone measurements using differential absorption lidar." In Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Upendra N. Singh and Kohei Mizutani. SPIE, 2005. http://dx.doi.org/10.1117/12.578168.

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Amblard, Victor, Timothy P. Osedach, Arnaud Croux, Andrew Speck, and John J. Leonard. "Lidar-Monocular Surface Reconstruction Using Line Segments." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9561437.

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Disney, M. I., P. Lewis, and M. Bouvet. "Quantifying Surface Reflectivity for Spaceborne Lidar Missions." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4778974.

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Reports on the topic "Réflectance lidar de surface"

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Andrews, James. Merging Surface Reconstructions of Terrestrial and Airborne LIDAR Range Data. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada538391.

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Carlberg, Matthew A. Fast Surface Reconstruction and Segmentation with Terrestrial LiDAR Range Data. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada538884.

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O'Dea, Annika, Nicholas Spore, Tanner Jernigan, et al. 3D measurements of water surface elevation using a flash lidar camera. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47496.

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This Coastal and Hydraulics Engineering technical note (CHETN) presents preliminary results from a series of tests conducted at the US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), in Duck, North Carolina, to explore the capabilities and limitations of the GSFL16K Flash Lidar Camera in nearshore science and engineering applications. The document summarizes the spatial coverage and density of data collected in three deployment scenarios and with a range of tuning parameters and provides guidance for future deploymen
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Carlberg, Matthew, James Andrews, Peiran Gao, and Avideh Zakhor. Fast Surface Reconstruction and Segmentation with Ground-Based and Airborne LIDAR Range Data. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada538860.

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Zechmann, J. M., and J. B. Salisbury. Lidar-derived surface elevation data for Dickason Highlands, Southcentral Alaska, collected August 14, 2024. Alaska Division of Geological & Geophysical Surveys, 2025. https://doi.org/10.14509/31536.

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Hara, Tetsu. Analysis of Steep and Breaking Ocean Surface Waves Using Data from an Airborne Scanning Lidar System. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada416563.

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Stevens, C. W., N. Short, and S. A. Wolfe. Seasonal surface displacement and highway embankment grade derived from InSAR and LiDAR, Highway 3 west of Yellowknife, Northwest Territories. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2012. http://dx.doi.org/10.4095/291383.

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Brinster, Gregory L., Mona Hodaei, Aser M. Eissa, et al. Leveraging LiDAR Intensity to Evaluate Roadway Pavement Marking Retroreflectivity. Purdue University, 2025. https://doi.org/10.5703/1288284317806.

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Clearly visible lane markings are important for all road users, particularly autonomous vehicles. In general, nighttime retroreflectivity is one of the most challenging marking visibility characteristics for agencies to monitor and maintain, particularly in cold weather climates when agency snowplows remove retroreflective material during winter operations. Traditional surface-applied paint and glass beads typically only last one season in climates with routine snowplow activity. Recently, transportation agencies in cold weather climates have begun deploying improved recessed, durable pavement
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Fassnacht, Steven, Kazuyoshi Suzuki, Jessica Sanow, et al. Snow surface roughness across spatio-temporal scales. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49199.

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The snow surface is at the interface between the atmosphere and Earth. The surface of the snowpack changes due to its interaction with precipitation, wind, humidity, short- and long-wave radiation, underlying terrain characteristics, and land cover. These connections create a dynamic snow surface that impacts the energy and mass balance of the snowpack, blowing snow potential, and other snowpack processes. Despite this, the snow surface is generally considered a constant parameter in many Earth system models. Data from the National Aeronautics and Space Administration (NASA) Cold Land Processe
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Berney, Ernest, Andrew Ward, and Naveen Ganesh. First generation automated assessment of airfield damage using LiDAR point clouds. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40042.

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Abstract:
This research developed an automated software technique for identifying type, size, and location of man-made airfield damage including craters, spalls, and camouflets from a digitized three-dimensional point cloud of the airfield surface. Point clouds were initially generated from Light Detection and Ranging (LiDAR) sensors mounted on elevated lifts to simulate aerial data collection and, later, an actual unmanned aerial system. LiDAR data provided a high-resolution, globally positioned, and dimensionally scaled point cloud exported in a LAS file format that was automatically retrieved and pro
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