Descripteur
Termes IGN > géomatique > données localisées > données localisées numériques > données laser > données lidar
données lidarSynonyme(s)levé par lidarVoir aussi |
Documents disponibles dans cette catégorie (1226)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Urban tree cover mapping with relief-corrected aerial imagery and lidar / B. Lehrbass in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 5 (May 2012)
[article]
Titre : Urban tree cover mapping with relief-corrected aerial imagery and lidar Type de document : Article/Communication Auteurs : B. Lehrbass, Auteur ; Jing Wang, Auteur Année de publication : 2012 Article en page(s) : pp 473 - 484 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre (flore)
[Termes IGN] arbre urbain
[Termes IGN] carte de la végétation
[Termes IGN] classification orientée objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] flore urbaine
[Termes IGN] fusion d'images
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] Ontario (Canada)
[Termes IGN] orthoimage
[Termes IGN] précision de la classification
[Termes IGN] zone urbaineRésumé : (Auteur) Urban tree canopy cover is often mapped by classifying high-resolution multispectral imagery. However, it can be difficult to differentiate low-lying vegetation from tree cover using optical data alone. Combining a lidar-derived Normalized Digital Surface Model (ndsm) improves classification accuracy, but the optical imagery is often imperfectly aligned with the NDSM. Aerial imagery is normally orthorectified using the ground elevation. However, tall objects in the orthorectified imagery still suffer from relief displacement. This can cause classification errors when lidar and the aerial imagery are combined. This study presents an approach for urban tree cover mapping composed of two parts: a method for correcting the relief displacement of trees in previously orthorectified aerial imagery, and an object-based classification method which combines relief-corrected multispectral aerial imagery with a lidar-derived NDSM. Using these methods, the tree cover was mapped for a 1,600 ha region of London, Ontario, Canada with improved positional and classification accuracy. Numéro de notice : A2012-233 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.5.473 En ligne : https://doi.org/10.14358/PERS.78.5.473 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31679
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 5 (May 2012) . - pp 473 - 484[article]An efficient point cloud management method based on a 3D R-tree / J. Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)
[article]
Titre : An efficient point cloud management method based on a 3D R-tree Type de document : Article/Communication Auteurs : J. Gong, Auteur ; Q. Zhu, Auteur ; R. Zhong, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 373 - 381 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre-R
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] octree
[Termes IGN] performance
[Termes IGN] semis de pointsRésumé : (Auteur) Vehicle-borne laser-scanned point clouds have become increasingly important 3D data sources in fields such as digital city modeling and emergency response management. Aiming at reducing the technical bottlenecks of management and visualization of very large point cloud data sets, this paper proposes a new spatial organization method called 3DOR-Tree, which integrates Octree and 3D R-Tree data structures. This method utilizes Octree's rapid convergence to generate R-Tree leaf nodes, which are inserted directly into the R-Tree, thus avoiding time-consuming point-by-point insertion operations. Furthermore, this paper extends the R-Tree structure to support LOD (level of detail) models. Based on the extended structure, a practical data management method is presented. Finally, an adaptive control method for LODS of point clouds is illustrated. Typical experimental results show that our method possesses quasi-real-time index construction speed, a good storage utilization rate, and efficient visualization performance. Numéro de notice : A2012-180 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.4.373 En ligne : https://doi.org/10.14358/PERS.78.4.373 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31627
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 4 (April 2012) . - pp 373 - 381[article]Automatic extraction of road markings from mobile Lidar point clouds / B. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)
[article]
Titre : Automatic extraction of road markings from mobile Lidar point clouds Type de document : Article/Communication Auteurs : B. Yang, Auteur ; Leyuan Fang, Auteur ; Qi Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 331 - 338 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] interpolation
[Termes IGN] lasergrammétrie
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] signalisation routièreRésumé : (Auteur) Among implicit information of laser points, the strength of reflection of laser points is closely related to the property of road materials which helps detecting road markings. This paper presents a novel approach to automatically extracting road markings from mobile lidar point clouds. An interpolation method is first used to generate a georeferenced feature image of the point cloud, which helps to isolate the points of road surfaces. Then, an algorithm is used to separate these points within a range according to their strength of reflection. The separated points are further segmented to remove non-road points based on height threshold. Finally, the outlines of road markings are extracted from the segmented points using the semantic knowledge of road markings. The results demonstrated that our method was very promising for automatic extraction of road markings from lidar point clouds collected by a land-based mobile lidar system, an Optech Lynx Mobile Mapper. Numéro de notice : A2012-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.4.331 En ligne : https://doi.org/10.14358/PERS.78.4.331 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31625
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 4 (April 2012) . - pp 331 - 338[article]Cell-based automatic deformation computation by analyzing terrestrial Lidar point clouds / J. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)
[article]
Titre : Cell-based automatic deformation computation by analyzing terrestrial Lidar point clouds Type de document : Article/Communication Auteurs : J. Wu, Auteur ; P.Y. Gilliéron, Auteur ; Bertrand Merminod, Auteur Année de publication : 2012 Article en page(s) : pp 317 - 329 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] érosion
[Termes IGN] lasergrammétrie
[Termes IGN] modèle de déformation tectonique
[Termes IGN] semis de pointsRésumé : (Auteur) This paper presents a cell-based approach for computing the deformation of a monitored object by analyzing point cloud data from terrestrial lidar. This approach can automatically generate an informative deformation description (called “deformation map”) with distinctive deformation characteristics for different partial areas. The approach consists of three major computing steps: (a) “split” - the space of the monitored object is divided into 3D uniform cells, (b) “detect” - deformation parameters for each cell (called “meta-deformation”) are estimated by comparing the point clouds in the cell sampled at Epochs I and II, and (c) “merge” - the adjacent cells with similar meta-deformation are combined together in a partial area with a consistent “sub-deformation.” The main contributions of this paper are: (a) a hybrid deformation model for incremental and comprehensive deformation representation, including metadeformation, sub-deformation and deformation map, (b) a systematic procedure of “split-detect-merge” to automatically and gradually estimate the hybrid deformation model, and (c) a complete validation with a couple of synthetic and real datasets. Numéro de notice : A2012-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.4.317 En ligne : https://doi.org/10.14358/PERS.78.4.317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31624
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 4 (April 2012) . - pp 317 - 329[article]Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)
[article]
Titre : Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment Type de document : Article/Communication Auteurs : Laven Naidoo, Auteur ; Moses Azong Cho, Auteur ; Renaud Mathieu, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 167 - 179 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Afrique du sud (état)
[Termes IGN] arbre (flore)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] image hyperspectrale
[Termes IGN] lasergrammétrie
[Termes IGN] parc naturel national
[Termes IGN] savaneRésumé : (Auteur) The accurate classification and mapping of individual trees at species level in the savanna ecosystem can provide numerous benefits for the managerial authorities. Such benefits include the mapping of economically useful tree species, which are a key source of food production and fuel wood for the local communities, and of problematic alien invasive and bush encroaching species, which can threaten the integrity of the environment and livelihoods of the local communities. Species level mapping is particularly challenging in African savannas which are complex, heterogeneous, and open environments with high intra-species spectral variability due to differences in geology, topography, rainfall, herbivory and human impacts within relatively short distances. Savanna vegetation are also highly irregular in canopy and crown shape, height and other structural dimensions with a combination of open grassland patches and dense woody thicket – a stark contrast to the more homogeneous forest vegetation. This study classified eight common savanna tree species in the Greater Kruger National Park region, South Africa, using a combination of hyperspectral and Light Detection and Ranging (LiDAR)-derived structural parameters, in the form of seven predictor datasets, in an automated Random Forest modelling approach. The most important predictors, which were found to play an important role in the different classification models and contributed to the success of the hybrid dataset model when combined, were species tree height; NDVI; the chlorophyll b wavelength (466 nm) and a selection of raw, continuum removed and Spectral Angle Mapper (SAM) bands. It was also concluded that the hybrid predictor dataset Random Forest model yielded the highest classification accuracy and prediction success for the eight savanna tree species with an overall classification accuracy of 87.68% and KHAT value of 0.843. Numéro de notice : A2012-199 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31646
in ISPRS Journal of photogrammetry and remote sensing > vol 69 (April 2012) . - pp 167 - 179[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012031 SL Revue Centre de documentation Revues en salle Disponible Laser scanning in heritage documentation: The scanning pipeline and its challenges / H. Ruther in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)PermalinkPermalinkMulti-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance / G. Wei in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkTerrestrial laser scanning for delineating in-stream boulders and quantifying habitat complexity measures / J. Resop in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)PermalinkTowards all-in-one photogrammetry / Dieter Fritsch in GIM international, vol 26 n° 4 (April 2012)PermalinkTree topology representation from TLS point clouds using depth-first search in voxel space / A. Schilling in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)PermalinkUsing multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest / O. Tsui in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkDigital measurements with 3D laser scanner: German scanning project / J. Rechenbach in Geoinformatics, vol 15 n° 2 (01/03/2012)PermalinkExtraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkHyperspectral unmixing based on mixtures of Dirichlet components / J. Nascimento in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)Permalink