Relevant bibliographies by topics / Réflectance lidar de surface

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Réflectance lidar de surface'

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Published: 25 May 2024

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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 homogénéité des traitements de séries temporelles d'images, le CNES a mis en place le programme Kalideos. Dans ce cadre, CS SI a développé et opère les chaines de traitement des images.Cet article présente les traitements appliqués aux images optiques des bases Kalideos (capteurs Spot et Formosat). Ces traitements permettent de convertir les produits de niveau 1A en ortho-images, donnant la réflectance mesurée au sommet de l'atmosphère et celle estimée au niveau de la surface après correction des effets atmosphériques.
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LIN, C. S. "Ocean surface profiling lidar." International Journal of Remote Sensing 17, no. 13 (September 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 (June 28, 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 et alcooliques ainsi que l’absorption d’eau. Ces différents tests permettent de prédire la digestibilité de l’amidon dans la partie supérieure du tractus digestif. L’analyse par réflectance dans le moyen infra-rouge pourrait devenir un outil de contrôle en ligne.
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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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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 (April 10, 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 Single Photon LiDAR (i) is less affected in this respect due to the high receiver sensitivity, and (ii) consequently delivers sufficient water surface echoes for precise high-resolution water surface reconstruction. After a review of the underlying sensor technology and the interaction of green laser light with water, we address the topic by comparing the surface responses of actual Single Photon LiDAR and Multi-Photon Topo-Bathymetric LiDAR datasets for selected horizontal water surfaces. The anticipated superiority of Single Photon LiDAR could not be verified in this study. While the mean deviations from a reference water level are less than 5 cm for surface models with a cell size of 10 m, systematic water level underestimation of 5–20 cm was observed for high-resolution Single Photon LiDAR based water surface models with cell sizes of 1–5 m. Theoretical photon counts obtained from simulations based on the laser-radar equation support the experimental data evaluation results and furthermore confirm the feasibility of Single Photon LiDAR based high-resolution water surface mapping when adopting specifically tailored flight mission parameters.
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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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Sedláček, Jozef, Ondřej Šesták, and Miroslava Sliacka. "Comparison of Digital Elevation Models by Visibility Analysis in Landscape." Acta Horticulturae et Regiotecturae 19, no. 2 (November 1, 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 comparison with LiDAR digital terrain model, ZABAGED model and field survey were 15.5 %, 17.3% and 20.9%, respectively.
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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 (February 25, 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 tide and high tide topo-bathymetric lidar surveys were completed in southwestern Nova Scotia, Canada. Comparison of lidar-derived seabed elevations with ground-truth data collected using a survey grade global navigation satellite system (GNSS) indicated the low tide survey data have a positive bias of 15 cm, likely resulting from the seaweed being draped over the surface. The high tide survey data did not exhibit this bias, although the suspended canopy floating on the water surface reduced the seabed lidar point density. Validation of lidar-derived seaweed heights indicated a mean difference of 30 cm with a root mean square error of 62 cm. The modelled surface area of seaweed was 28% greater in the lidar model than the satellite model. The average lidar-derived biomass estimate was within one standard deviation of the mean biomass measured in the field. The lidar method tends to overestimate the biomass compared to field measurements that were spatially biased to the mid-intertidal level. This study demonstrates an innovative and cost-effective approach that uses a single high tide bathymetric lidar survey to map the height and biomass of dense macroalgae.
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Telling, Jennifer, Craig Glennie, Andrew Fountain, and David Finnegan. "Analyzing Glacier Surface Motion Using LiDAR Data." Remote Sensing 9, no. 3 (March 17, 2017): 283. http://dx.doi.org/10.3390/rs9030283.

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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 sources naturelles, comme les feux de forêt saisonniers ou le transport vers le nord des poussières désertiques, mais également des sources anthropiques comme celles des zones exploitations d’hydrocarbures ou le transport à longue distance des émissions du Nord de la Chine. Afin de contribuer à l’amélioration de cette caractérisation des sources d’aérosol en Sibérie, nous avons dans un premier temps analysé les mesures de deux campagnes aéroportés réalisées sur des distances de plusieurs milliers de km en juillet 2013 et juin 2017. L’avion était équipé d’un lidar à rétrodiffusion à 532 nm ainsi de mesures in-situ de monoxyde de carbone (CO), de carbone suie (BC) et des distributions en taille des aérosols. Ces observations ont été étudiées en synergie avec celle du lidar spatial CALIOP et des missions MODIS et IASI. La gamme d'altitude des couches d'aérosols et le rôle de l’âge sur les propriétés optiques (épaisseur optique (AOD532), dépolarisation, rapport de couleur) sont discutés pour chaque type d'aérosol. Les résultats d’un vol au-dessus des régions d’extraction du gaz correspond au plus fortes AOD532, et des concentrations en BC supérieure à celle des émissions des zones urbaines et a permis une estimation du rapport lidar de ces panaches d'aérosols mal documentés dans la littérature. La deuxième partie du travail a consisté à proposer une alternative à la restitution indirecte de l’AOD532 par l’instrument CALIOP à partir de l’inversion du signal lidar de rétrodiffusion atténué. Cette méthode utilise la réflectance du signal lidar de CALIOP par la surface et a déjà été utilisée au-dessus des océans ou des nuages d’eau liquide optiquement opaques pour calculer une valeur AOD. Dans ce travail, nous avons ainsi développé et évalué une restitution des AOD à partir de la réflectance CALIOP de surface pour les zones continentales. Deux méthodologies ont été utilisées afin de déterminer la réflectance lidar de surface non atténuée par les aérosols: (i) sélection des observations CALIOP en condition de ciel clair sur 7 ans d’observation (ii) extrapolation de la relation de linéarité entre la réflectance lidar de surface atténuée et la transmission atmosphérique. Si ces deux méthodes donnent de bons résultats dans les zones de faible réflectance lidar de surface (< 0.75 sr-1) la première méthode n’est pas utilisable sur les zones désertiques. L’utilisation de ces AOD lidar mesurées directement au-dessus des surfaces continentales permet d’améliorer le biais (|ME| < 0.034) et la dispersion (< 0.145) en comparaison aux observations MODIS. Ceci améliore beaucoup les résultats des comparaisons CALIOP-MODIS obtenus avec la restitution indirecte des AOD une analyse des profils verticaux de rétrodiffusion lidar atténuée avec un biais < 0.174 et une dispersion < 0.234
Knowledge of the distribution and physico-chemical properties of aerosol particles in the troposphere has been identified by the Intergovernmental Panel on Climate Change (IPCC) as the main source of uncertainty in the study of climate change. Characterization of the types, optical properties and vertical distribution of aerosols at the regional scale is needed to reduce this source of uncertainty and some areas such as Siberia are still poorly documented. Aerosol concentrations in Siberia depend on natural sources, such as seasonal forest fires or northward transport of desert dust, but also on anthropogenic sources such as those from hydrocarbon mining areas or long-range transport of emissions from northern China. In order to contribute to the improvement of this characterization of aerosol sources in Siberia, we first analyzed the measurements of two airborne campaigns carried out over distances of several thousand km in July 2013 and June 2017. The aircraft was equipped with a back-scattering lidar at 532 nm, as well as in-situ measurements of carbon monoxide (CO), black carbon (BC) and aerosol size distributions. These observations were studied in synergy with those of the CALIOP spaceborne lidar and the MODIS and IASI missions. The altitude range of the aerosol layers and the role of age on the optical properties (optical thickness (AOD532), depolarization, color ratio) are discussed for each type of aerosol. The results of a flight over the gas extraction regions corresponded to the highest AOD532 and higher BC concentrations than the emissions from urban areas and allowed an estimation of the lidar ratio of these aerosol plumes poorly documented in the literature. The second part of the work consisted in proposing an alternative to the indirect restitution of the AOD532 by the CALIOP instrument from the inversion of the attenuated back-scattering lidar signal. This method uses the surface reflectance of the CALIOP lidar signal and has already been used over oceans or optically opaque liquid water clouds to calculate an AOD value. In this work, we have thus developed and evaluated an AOD restitution from the CALIOP surface reflectance for continental areas. Two methodologies were used to determine the surface lidar reflectance not attenuated by aerosols: (i) selection of CALIOP observations under clear sky conditions over 7 years of observation (ii) extrapolation of the linearity relationship between attenuated surface lidar reflectance and atmospheric transmission. If these two methods give good results in areas of low surface lidar reflectance (< 0.75sr-1), the first method is not usable in desert areas. The use of these LIDAR AOD measured directly over continental surfaces improves the bias (|ME| < 0.034) and dispersion (< 0.145) compared to MODIS observations. This greatly improves the results of the CALIOP-MODIS comparisons obtained with the indirect restitution of the AODs an analysis of the vertical profiles of attenuated lidar backscatter with a bias < 0.174 and dispersion < 0.234
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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 reconstruction de modèles d’attributs de placettes forestières : le sol etla structure ligneuse des arbres (i.e. troncs et branches principales). En pratique, nos approches modélisent le problème par des surfaces implicites construites à partir de fonctions à base radiale pour faire face à la forte hétérogénéité spatiale du nuage de points Lidar terrestre
In recent years, the capacity of LiDAR technology to capture detailed information about forests structure has attracted increasing attention in the field of forest science. In particular, the terrestrial LiDAR arises as a promising tool to retrieve geometrical characteristics of trees at a millimeter level.This thesis studies the surface reconstruction problem from scattered and unorganized point clouds, captured in forested environment by a terrestrial LiDAR. We propose a sequence of algorithms dedicated to the reconstruction of forests plot attributes model: the ground and the woody structure of trees (i.e. the trunk and the main branches). In practice, our approaches model the surface with implicit function build with radial basis functions to manage the homogeneity and handle the noise of the sample data points
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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 samplesand calculates the area under it, has been developed and described. The calculated area values are validated after comparing them to their theoretically predicted counterpart values. Methods to retrieve aerosol optical depths (AODs) from these calculated areas are described and retrieval results are presented, including retrieval comparison with independent AOD measurements made by an airborne High Spectral Resolution Lidar (HSRL) that yielded quite good agreement. Techniques and results are also presented on using the spectral ratios of the surface response areas to determine spectral ratios of aerosol round-trip transmission and AOD spectral difference, without need of a specific/accurate ocean-surface reflectance model.
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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 thesis describes a method for accurate classification of bare ground, water body, roads, vegetation, and structures using LiDAR data and aerial Infrared imagery. The most basic step for any terrain modeling application is filtering which is classification of ground and non-ground points. We present an integrated systematic method that makes classification of terrain and non-terrain points effective. Our filtering method uses the geometric feature of the triangle meshes created from LiDAR samples and calculate the confidence for every point. Geometric homogenous blocks and confidence are derived from TIN model and gridded LiDAR samples. The results from two representations are used in a classifier to determine if the block belongs ground or otherwise. Another important step is detection of water body, which is based on the LiDAR sample density of the region. Objects like tress and bare ground are characterized by the geometric features present in the LiDAR and the color features in the infrared imagery. These features are fed into a SVM classifier which detects bare-ground in the given region. Similarly trees are extracted using another trained SVM classifier. Once we obtain bare-grounds and trees, roads are extracted by removing the bare grounds. Structures are identified by the properties of non-ground segments. Experiments were conducted using LiDAR samples and Infrared imagery from the city of New Orleans. We evaluated the influence of different parameters to the classification. Water bodies were extracted successfully using density measures. Experiments showed that fusion of geometric properties and confidence levels resulted into efficient classification of ground and non-ground regions. Classification of vegetation using SVM was promising and effective using the features like height variation, HSV, angle etc. It is demonstrated that our methods successfully classified the region by using LiDAR data in a complex urban area with high-rise buildings.
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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 dissertation introduces novel algorithms and frameworks based on statistical techniques and image analysis in order to segment and extract surfaces from sparse noisy point clouds. We introduce an adaptive method for mapping point clouds onto an image grid followed by a contour detection approach that is based on an enhanced version of region-based Active Contours Without Edges (ACWE). We also proposed a noise reduction method using Bayesian approach and incorporated it, along with other noise reduction approaches, into a joint framework that produces robust results. We combined the aforementioned techniques with a statistical surface refinement method to introduce a novel framework to detect ground and canopy surfaces in micropulse photon-counting LiDAR data. The algorithm is fully automatic and uses no prior elevation or geographic information to extract surfaces. Moreover, we propose a novel segmentation framework for noisy point clouds in the plane based on a Markov random field (MRF) optimization that we call Point Cloud Densitybased Segmentation (PCDS). We also developed a large synthetic dataset of in plane point clouds that includes either a set of randomly placed, sized and oriented primitive objects (circle, rectangle and triangle) or an arbitrary shape that forms a simple approximation for the LiDAR point clouds. The experiment performed on a large number of real LiDAR and synthetic point clouds showed that our proposed frameworks and algorithms outperforms the state-of-the-art algorithms in terms of segmentation accuracy and surface RMSE.
Ph. D.
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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 generate irregular two-dimensional channel grids from hydrographic cross-sections at any desired resolution. Hydraulic spline output grids can be easily merged with datasets of higher resolution, such as LIDAR data, to build a complete model of channel geometry and overbank topography. In testing, the hydraulic spline algorithm faithfully reproduces elevations of known input cross-section points where they exist, while generating a smooth transition between known cross-sections. The algorithm performs particularly well compared to traditional techniques with respect to aesthetics and accuracy when input data is sparse. These qualities make the hydraulic spline an ideal choice for practical applications where available data may be limited due to historic or budgetary reasons.
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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 terrestrial LiDAR. Field, laboratory and numerical experiments have been carried out to test the precision and accuracy of the technique, and calibrations have been developed for correcting field observations of surface roughness for known biases. Results obtained using this technique have been applied in several microwave remote sensing and electromagnetic-wave scattering model studies of snow-covered and melting sea ice. Terrestrial and satellite LiDAR observations are acquired and combined in a further study to examine how sea ice surface topography regulates the melting of ice during the Arctic summer. Observations from a field program in the Canadian Arctic show that minor variations in the roughness of pre-melt sea ice topography can affect significant variations in the melt pond coverage at the ice surface in summer. Numerical simulations are used to develop a quantitative understanding of these findings and, when applied to satellite observations, explain most of the spatial variation in Arctic summer ice melting rates. Results suggest that a recent reduction in sea ice roughness, caused by progressive changes in the type of sea ice resident in the Arctic Ocean, has accelerated the summer melting and decline of the Arctic sea ice cover.
May 2016
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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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Theory of reflectance and emittance spectroscopy. Cambridge [England]: Cambridge University Press, 1993.

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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, 177–80. Berlin, Heidelberg: 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, 112–21. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1095-9_11.

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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, 689–95. Berlin, Heidelberg: 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, 185–90. Singapore: 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, 451–54. Cham: 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, 463–71. Cham: 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, 147–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01440-7_34.

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Trouillet, Vincent, Patrick Chazette, Jacques Pelon, and Cyrille Flamant. "Assessment of the Oceanic Surface Reflectance by Airborne Lidar to Improve a Stable Inversion Technique." In Advances in Atmospheric Remote Sensing with Lidar, 47–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60612-0_12.

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Mukherjee, Aritra, Sourya Dipta Das, Jasorsi Ghosh, Ananda S. Chowdhury, and Sanjoy Kumar Saha. "Fast Geometric Surface Based Segmentation of Point Cloud from Lidar Data." In Lecture Notes in Computer Science, 415–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34869-4_45.

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Zhao, Chunhui, Zhenhui Yi, Xiaolei Hou, and Jinwen Hu. "Lidar-Artificial-Marker Odometry for a Surface Climbing Robot via Factor Graph." In Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022), 503–12. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0479-2_47.

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Conference papers on the topic "Réflectance lidar de surface"

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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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Sheehan, Michael P., Julian Tachella, and Mike E. Davies. "Surface Detection for Sketched Single Photon Lidar." In 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9616208.

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Maillard, Jean-Michel, Eric Ruben, Prabhu Thiagarajan, Brian Caliva, Linda West, and Robert Walker. "Lasertel VCSEL development progress for automotive lidar." In Vertical-Cavity Surface-Emitting Lasers XXIV, edited by Chun Lei and Luke A. Graham. SPIE, 2020. http://dx.doi.org/10.1117/12.2547523.

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Wang, K., L. Yao, and J. Lin. "Ground Surface Deformation Detection from Far Satellite SAR to UAV LiDAR and Terrestrial Lidar." In 5th Asia Pacific Meeting on Near Surface Geoscience & Engineering. European Association of Geoscientists & Engineers, 2023. http://dx.doi.org/10.3997/2214-4609.202378038.

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Guenther, Gary C., Paul E. LaRocque, and W. Jeff Lillycrop. "Multiple surface channels in Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS) airborne lidar." In Ocean Optics XII, edited by Jules S. Jaffe. SPIE, 1994. http://dx.doi.org/10.1117/12.190084.

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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. Fort Belvoir, VA: Defense Technical Information Center, May 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. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada538884.

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O'Dea, Annika, Nicholas Spore, Tanner Jernigan, Brittany Bruder, Ian Conery, Jessamin Straub, and Katherine Brodie. 3D measurements of water surface elevation using a flash lidar camera. Engineer Research and Development Center (U.S.), August 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 deployments and data-collection efforts.
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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. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada538860.

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Hara, Tetsu. Analysis of Steep and Breaking Ocean Surface Waves Using Data from an Airborne Scanning Lidar System. Fort Belvoir, VA: Defense Technical Information Center, July 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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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.), March 2021. http://dx.doi.org/10.21079/11681/40042.

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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 processed using volumetric detection algorithms developed in the MATLAB software environment. Developed MATLAB algorithms used a three-stage filling technique to identify the boundaries of craters first, then spalls, then camouflets, and scaled their sizes based on the greatest pointwise extents. All pavement damages and their locations were saved as shapefiles and uploaded into the GeoExPT processing environment for visualization and quality control. This technique requires no user input between data collection and GeoExPT visualization, allowing for a completely automated software analysis with all filters and data processing hidden from the user.
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Gavillot, Y., J. Lonn, M. Stickney, and A. Hidy. Quaternary slip rates and most recent surface rupture of the Bitterroot fault, western Montana. Montana Bureau of Mines and Geology, February 2023. http://dx.doi.org/10.59691/vzpp8697.

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We present new detailed mapping using lidar with measurements of deformation and in situ age data (CRN 10Be) to constrain Pleistocene-early Holocene fault slip rates of the Bitterroot fault. Our study area is located in the Southern Bitterroot near Lake Como. Improved knowledge of the fault slip rates provides new constraints on the characterization of the late Quaternary fault history and earthquake potential. Our results support ongoing efforts to update geological parameters and improve regional deformation models used in the NSHM and USGS Quaternary Fault and Fold Database in the Intermountain West, as well as local earthquake hazards assessment for the Missoula-Bitterroot valleys and its infrastructures.
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Janet Intrieri and Mathhew Shupe. Using Radar, Lidar and Radiometer Data from NSA and SHEBA to Quantify Cloud Property Effects on the Surface Heat Budget in the Arctic. Office of Scientific and Technical Information (OSTI), January 2005. http://dx.doi.org/10.2172/877535.

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Gavillot, Yann G. Quaternary fault map of Jefferson County, southwest Montana. Montana Bureau of Mines and Geology, November 2022. http://dx.doi.org/10.59691/vzim1555.

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This Quaternary fault map identifies new and existing faults that demonstrate evidence of earthquake surface ruptures based on lidar data, geomorphic and topographic analyses, field checks, and, when available, published geological maps.
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