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Titre : Topographic laser ranging and scanning : principles and processing Type de document : Guide/Manuel Auteurs : Jie Shan, Éditeur scientifique ; Charles K. Toth, Éditeur scientifique Mention d'édition : Second edition Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2018 ISBN/ISSN/EAN : 978-1-315-15438-1 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] contrôle qualité
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de terrain
[Termes IGN] orthorectification
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] télémétrie laser terrestreIndex. décimale : 33.80 Lasergrammétrie Résumé : (éditeur) This Second Edition, provides a comprehensive discussion of topographic LiDAR principles, systems, data acquisition, and data processing techniques. This edition presents an introduction and summary of various LiDAR systems and their principles and addresses the operational principles of the different components and ranging methods of LiDAR systems. It discusses the subsequent geometric processing of LiDAR data, with particular attention to quality, accuracy, and meeting standards and addresses the theories and practices of information extraction from LiDAR data, including terrain surface generation, forest inventory, orthoimage generation, building reconstruction, and road extraction. Written by leaders in the field, this comprehensive compilation is a must-have reference book for senior undergraduate and graduate students majoring or working in diverse disciplines, such as geomatics, geodesy, natural resources, urban planning, computer vision, and computer graphics. It is also vital resource for researchers who are interested in developing new methods and need in-depth knowledge of laser scanning and data processing and other professionals may gain the same from the broad topics addressed in this book. Note de contenu : 1. Introduction to Laser Ranging, Profiling, and Scanning
2. Terrestrial Laser Scanners
3. Airborne and Spaceborne Laser Profilers and Scanners
4. LiDAR Systems and Calibration
5. Pulsed Laser Altimeter Ranging Techniques and Implications for Terrain Mapping
6. Georeferencing Component of LiDAR Systems
7. Full-Waveform Analysis for Pulsed Laser Systems
8. Strip Adjustment
9. Accuracy, Quality Assurance, and Quality Control of Light Detection and Ranging Mapping
10. Data Management of Light Detection and Ranging
11. LiDAR Data Filtering and Digital Terrain Model Generation
12. Forest Inventory Using Laser Scanning
13. Integration of LiDAR and Photogrammetric Data: Triangulation and Orthorectification
14. Feature Extraction from Light Detection and Ranging Data in Urban Areas
15. Global Solutions to Building Segmentation and Reconstruction
16. Building and Road Extraction from LiDAR Data
17. Progressive Modeling of 3D Building Rooftops from Airborne LiDAR and Imagery
18. A Framework for Automated Construction of Building Models from Airborne LiDAR Measurements
19. Quality of Buildings Extracted from Airborne Laser Scanning Data—Results of an Empirical Investigation on 3D Building ReconstructionNuméro de notice : 26946 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/URBANISME Nature : Manuel DOI : 10.1201/9781315154381 En ligne : https://doi.org/10.1201/9781315154381 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102179 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 26946-01 33.80 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible Weighted simplicial complex reconstruction from mobile laser scanning using sensor topology / Stéphane Guinard (2018)
Titre : Weighted simplicial complex reconstruction from mobile laser scanning using sensor topology Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Bruno Vallet , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2018 Conférence : CFPT 2018, Conférence Française de Photogrammétrie et de Télédétection 25/06/2018 28/06/2018 Champs-sur-Marne France Open Access Proceedings Importance : 8 p. Note générale : bibliographie
The authors would like to acknowledge the DGA for their financial support of this work.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] complexe simplicial
[Termes IGN] coplanarité
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] instrument embarqué
[Termes IGN] reconstruction 3D
[Termes IGN] relation spatiale
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) We propose a new method for the reconstruction of simplicial complexes (combining points, edges and triangles) from 3D point clouds from Mobile Laser Scanning (MLS). Our method uses the inherent topology of the MLS sensor to define a spatial adjacency relationship between points. We then investigate each possible connexion between adjacent points, weighted according to its distance to the sensor, and filter them by searching collinear structures in the scene, or structures perpendicular to the laser beams. Next, we create and filter triangles for each triplet of self-connected edges and according to their local planarity. We compare our results to an unweighted simplicial complex reconstruction. Numéro de notice : C2018-017 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésNat DOI : sans Date de publication en ligne : 25/06/2018 En ligne : https://rfiap2018.ign.fr/sites/default/files/ARTICLES/CFPT2018/Oraux/CFPT2018_pa [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90388 Documents numériques
en open access
Weighted simplicial complex reconstruction ... - pdf éditeurAdobe Acrobat PDF Object-based classification of terrestrial laser scanning point clouds for landslide monitoring / Andreas Mayr in Photogrammetric record, vol 32 n° 160 (December 2017)
[article]
Titre : Object-based classification of terrestrial laser scanning point clouds for landslide monitoring Type de document : Article/Communication Auteurs : Andreas Mayr, Auteur ; Martin Rutzinger, Auteur ; Magnus Bremer, Auteur ; Sander J. Oude Elberink, Auteur ; Felix Stumpf, Auteur ; Clemens Geitner, Auteur Année de publication : 2017 Conférence : VGC 2016, 2nd virtual geoscience conference 22/09/2016 23/09/2016 Bergen Norvège Proceedings Wiley Article en page(s) : pp 377 - 397 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] classification orientée objet
[Termes IGN] compréhension de l'image
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] effondrement de terrain
[Termes IGN] relation topologique 3D
[Termes IGN] semis de points
[Termes IGN] surveillance géologiqueRésumé : (auteur) Terrestrial laser scanning (TLS) is often used to monitor landslides and other gravitational mass movements with high levels of geometric detail and accuracy. However, unstructured TLS point clouds lack semantic information, which is required to geomorphologically interpret the measured changes. Extracting meaningful objects in a complex and dynamic environment is challenging due to the objects' fuzziness in reality, as well as the variability and ambiguity of their patterns in a morphometric feature space. This work presents a point‐cloud‐based approach for classifying multitemporal scenes of a hillslope affected by shallow landslides. The 3D point clouds are segmented into morphologically homogeneous and spatially connected parts. These segments are classified into seven target classes (scarp, eroded area, deposit, rock outcrop and different classes of vegetation) in a two‐step procedure: a supervised classification step with a machine‐learning classifier using morphometric features, followed by a correction step based on topological rules. This improves the final object extraction considerably. Numéro de notice : A2017-899 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12215 Date de publication en ligne : 13/12/2017 En ligne : https://doi.org/10.1111/phor.12215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89522
in Photogrammetric record > vol 32 n° 160 (December 2017) . - pp 377 - 397[article]Algebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)
[article]
Titre : Algebraic method to speed up robust algorithms: example of laser-scanned point clouds Type de document : Article/Communication Auteurs : B. Palancz, Auteur ; Joseph L. Awange, Auteur ; T. Lovas, Auteur ; R. Lewis, Auteur ; B. Molnar, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 408 - 418 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bases de Gröbner
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] valeur aberranteRésumé : (auteur) Surface reconstruction from point clouds generated by laser scanning technology has become a fundamental task in many fields of geosciences, such as robotics, computer vision, digital photogrammetry, computational geometry, digital building modelling, forest planning and operational activities. Point clouds produced by laser scanning, however, are limited due to the occurrence of occlusions, multiple reflectance and noise, and off-surface points (outliers), thus necessitating the need for robust fitting techniques. In this contribution, a fast, non-iterative and data invariant algebraic algorithm with constant O(1) complexity that fits planes to point clouds in the total least squares sense using Gaussian-type error distribution is proposed. The maximum likelihood estimator method is used, resulting in a multivariate polynomial system that is solved in an algebraic way. It is shown that for plane fitting when datasets are affected heavily by outliers, the proposed algebraic method can be embedded into the framework of robust methods like the Danish or the RANdom SAmple Consensus methods and computed in parallel to provide rigorous algebraic fitting with significantly reduced running times. Compared to the embedded traditional singular value decomposition and principal component analysis approaches, the performance of the proposed algebraic algorithm demonstrated its efficiency on both synthetic data and real laser-scanned measurements. The evaluation of a symbolic algebraic formula is practically independent of the values of its coefficients; however, the computation of the coefficients depends on the complexity of the data. Since the main advantage of the symbolic solution is its non-requirement of numerical iteration, the data complexity will have weak influence on the speed-up. The novelty of the proposed method is the use of algebraic technique in a robust plane fitting algorithm that could be applied to remote sensing data analysis/delineation/classification. In general, the method could be applied to most plane fitting problems in the geoscience field. Numéro de notice : A2017-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/00396265.2016.1183939 En ligne : https://doi.org/10.1080/00396265.2016.1183939 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89109
in Survey review > vol 49 n° 357 (December 2017) . - pp 408 - 418[article]Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
[article]
Titre : Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds Type de document : Article/Communication Auteurs : Paweł Hawryło, Auteur ; Piotr Tompalski, Auteur ; Piotr Wezyk, Auteur Année de publication : 2017 Article en page(s) : pp 686 - 696 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus sylvestris
[Termes IGN] régression linéaire
[Termes IGN] régression multiple
[Termes IGN] semis de points
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Recent research has shown that image-derived point clouds (IPCs) are a highly competitive alternative to airborne laser scanning (ALS) data in the context of selected forest inventory activities. However, there is still a need for investigating different kinds of aerial images used for point cloud generation. This study compares the effectiveness of IPCs derived from true colour (RGB) and colour infrared (CIR) aerial images with ALS data for growing stock volume estimation of single canopy layer Scots pine stands. A multiple linear regression method was used to create predictive models. All models predicted growing stock volume with low root mean square errors – ALS: 15.2%, IPC-CIR: 17.0% and IPC-RGB: 17.5%. The following variables for each data type were found to be the most robust: ALS – mean height of points, percentage of all returns above mean height of points, interquartile range of point heights; IPC-CIR – mean height of points, percentage of all returns above mode height of points, canopy relief ratio; IPC-RGB – mean height of points and canopy relief ratio. Our results show that for single canopy layer Scots pine dominated stands it is possible to predict growing stock volume using IPCs with a comparable accuracy as using ALS data. The comparable performance of IPC-RGB and IPC-CIR based models suggests that a mixed usage of RGB and CIR data in retrospective studies could be possible. Numéro de notice : A2017-904 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx026 En ligne : https://doi.org/10.1093/forestry/cpx026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93205
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 686 - 696[article]Building extraction from fused LiDAR and hyperspectral data using Random Forest Algorithm / Saeid Parsian in Geomatica, vol 71 n° 4 (December 2017)PermalinkEstimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)PermalinkLow-cost warning system for the monitoring of the Corinth Canal / George Hloupis in Applied geomatics, vol 9 n° 4 (December 2017)PermalinkModélisation d'un oppidum sous couvert végétal dense, en Eure-et-Loir, par un LiDAR aéroporté par drone / Isabelle Heitz in XYZ, n° 153 (décembre 2017 - février 2018)PermalinkPairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game / Dawei Zai in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkRemotely sensed forest habitat structures improve regional species conservation / Christian Reichsteiner in Remote sensing in ecology and conservation, vol 3 n° 4 (December 2017)PermalinkSNCF Réseau : de l'acquisition 3D à la diffusion de la donnée / Mathieu Regul in XYZ, n° 153 (décembre 2017 - février 2018)PermalinkSuivi topographique côtier au moyen d’un système LiDAR mobile terrestre : exemple d’une recharge sédimentaire de plage / Stéfanie Van-Wierts in Geomatica, vol 71 n° 4 (December 2017)PermalinkTerrestrial laser scanning reveals differences in crown structure of Fagus sylvatica in mixed vs. pure European forests / Ignacio Barbeito in Forest ecology and management, vol 405 (1 December 2017)PermalinkAn examination of diameter density prediction with k-NN and airborne lidar / Jacob L. Strunk in Forests, vol 8 n° 11 (November 2017)PermalinkBIM en réhabilitation : l'atout drone / Marielle Mayo in Géomètre, n° 2152 (novembre 2017)PermalinkChangement climatique et risque inondation / William Halbecq in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkFusion of hyperspectral and LiDAR data using sparse and low-rank component analysis / Behnood Rasti in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)PermalinkMapping the height and spatial cover of features beneath the forest canopy at small-scales using airborne scanning discrete return Lidar / Matthew Sumnall in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkTree species classification using within crown localization of waveform LiDAR attributes / Rosmarie Blomley in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkBayesian graph-cut optimization for wall surfaces reconstruction in indoor environments / Georgios-Tsampikos Michailidis in The Visual Computer, vol 33 n° 10 (October 2017)PermalinkMulti-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data / Hooman Latifi in Forestry, an international journal of forest research, vol 90 n° 4 (October 2017)PermalinkRegistration of images to Lidar and GIS data without establishing explicit correspondences / Gabor Barsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)PermalinkSignificant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)PermalinkOccupancy modelling for moving object detection from Lidar point clouds: A comparative study / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W4 (September 2017)PermalinkBuilding on firm foundations / Dominik Wesołowski in GEO: Geoconnexion international, vol 16 n° 9 (September 2017)PermalinkDrones et photogrammétrie : Un outil dans l’ADN de la profession / Benoît Greuzat in Géomètre, n° 2150 (septembre 2017)PermalinkEffects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling / Yi Hong in Applied sciences, vol 7 n° 9 (September 2017)PermalinkForest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India / S.M. Ghosh in Applied geomatics, vol 9 n° 3 (September 2017)PermalinkImpact of spatial correlations on the surface estimation based on terrestrial laser scanning / Tobias Jurek in Journal of applied geodesy, vol 11 n° 3 (September 2017)PermalinkPoint cloud refinement with self-calibration of a mobile multibeam lidar sensor / Houssem Nouira in Photogrammetric record, vol 32 n° 159 (September 2017)PermalinkPrecision estimation of the angular resolution of terrestrial laser scanners / Xijiang Chen in Photogrammetric record, vol 32 n° 159 (September 2017)PermalinkTerrain model reconstruction from terrestrial LiDAR data using radial basis functions / Jules Morel in IEEE Computer graphics and applications, vol 37 n° 5 ([01/09/2017])PermalinkUrban building reconstruction from raw LiDAR point data / Cheng Yi in Computer-Aided Design, vol 9x (2017)PermalinkVisual inspection of fire-damaged concrete based on terrestrial laser scanner data / Wallace Mukupa in Applied geomatics, vol 9 n° 3 (September 2017)PermalinkAutomatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning / Tim Ritter in Forests, vol 8 n° 8 (August 2017)PermalinkHybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar / Sören Holm in Remote sensing of environment, vol 197 (August 2017)PermalinkImage matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)PermalinkJoint classification and contour extraction of large 3D point clouds / Timo Hackel in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkReducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)Permalink3D building roof reconstruction from airborne LiDAR point clouds : a framework based on a spatial database / Rujun Cao in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkApplication of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index / Titta Majasalmi in International journal of applied Earth observation and geoinformation, vol 59 (July 2017)PermalinkNe plus négliger le recul des falaises méditerranéennes / Marielle Mayo in Géomètre, n° 2149 (juillet - août 2017)PermalinkPredicting stem total and assortment volumes in an industrial pinus taeda L. forest plantation using airborne laser scanning data and random forest / Carlos Alberto Silva in Forests, vol 8 n° 7 (July 2017)PermalinkSafe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkAngular reflectance of leaves with a dual-wavelength terrestrial lidar and its implications for leaf-bark separation and leaf moisture estimation / Steven Hancock in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)PermalinkApport des plans directeurs et de l’outil LiDAR aéroporté pour la caractérisation des impacts morphologiques de la Grande Guerre : exemple de la cote 108 (Berry‑au‑Bac, France) / Pierre Taborelli in Géomorphologie, vol. 23 n° 2 ([01/06/2017])PermalinkPermalinkAutomation of point cloud processing to increase the deformation monitoring accuracy / Ján Erdélyi in Applied geomatics, vol 9 n° 2 (June 2017)PermalinkDetection of inconsistencies in geospatial data with geostatistics / Adriana Maria Rocha Trancoso Santos in Boletim de Ciências Geodésicas, vol 23 n° 2 (abr - jun 2017)Permalink