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Modélisation 3D de la végétation sur le territoire de Rennes Métropole (Partie 2) / Coralie Leblan in Géomatique expert, n° 124 (septembre - octobre 2018)
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Titre : Modélisation 3D de la végétation sur le territoire de Rennes Métropole (Partie 2) Type de document : Article/Communication Auteurs : Coralie Leblan, Auteur ; Christelle Gibon, Auteur Année de publication : 2018 Article en page(s) : pp 42 - 54 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] flore urbaine
[Termes IGN] houppier
[Termes IGN] maquette numérique
[Termes IGN] métropole
[Termes IGN] modélisation 3D
[Termes IGN] R (langage)
[Termes IGN] reconstruction 3D
[Termes IGN] Rennes
[Termes IGN] semis de pointsRésumé : (éditeur) Le service SIG de la métropole de Rennes cherche à reconstituer, à partir d’un nuage de points LiDAR aérien, des modèles réalistes de végétation urbaine afin d’alimenter sa maquette 3D. Numéro de notice : A2018-423 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90893
in Géomatique expert > n° 124 (septembre - octobre 2018) . - pp 42 - 54[article] Voir aussiExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité IFN-001-P002084 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Scalable individual tree delineation in 3D point clouds / Jinhu Wang in Photogrammetric record, vol 33 n° 163 (September 2018)
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Titre : Scalable individual tree delineation in 3D point clouds Type de document : Article/Communication Auteurs : Jinhu Wang, Auteur ; Roderik Lindenbergh, Auteur ; Massimo Menenti, Auteur Année de publication : 2018 Article en page(s) : pp 315 - 340 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement
[Termes IGN] arbre (flore)
[Termes IGN] délimitation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire de la végétation
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Manually monitoring and documenting trees is labour intensive. Lidar provides a possible solution for automatic tree‐inventory generation. Existing approaches for segmenting trees from original point cloud data lack scalable and efficient methods that separate individual trees sampled by different laser‐scanning systems with sufficient quality under all circumstances. In this study a new algorithm for efficient individual tree delineation from lidar point clouds is presented and validated. The proposed algorithm first resamples the points using cuboid (modified voxel) cells. Consecutively connected cells are accumulated by vertically traversing cell layers. Trees in close proximity are identified, based on a novel cell‐adjacency analysis. The scalable performance of this algorithm is validated on airborne, mobile and terrestrial laser‐scanning point clouds. Validation against ground truth demonstrates an improvement from 89% to 94% relative to a state‐of‐the‐art method while computation time is similar. Numéro de notice : A2018-619 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12247 Date de publication en ligne : 16/07/2018 En ligne : https://doi.org/10.1111/phor.12247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92863
in Photogrammetric record > vol 33 n° 163 (September 2018) . - pp 315 - 340[article]Three-dimensional building façade segmentation and opening area detection from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)
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[article]
Titre : Three-dimensional building façade segmentation and opening area detection from point clouds Type de document : Article/Communication Auteurs : S.M. Iman Zolanvari, Auteur ; Debra F. Laefer, Auteur ; Atteyeh S. Natanzi, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 149 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] toitRésumé : (Auteur) Laser scanning generates a point cloud from which geometries can be extracted, but most methods struggle to do this automatically, especially for the entirety of an architecturally complex building (as opposed to that of a single façade). To address this issue, this paper introduces the Improved Slicing Method (ISM), an innovative and computationally-efficient method for three-dimensional building segmentation. The method is also able to detect opening boundaries even on roofs (e.g. chimneys), as well as a building’s overall outer boundaries using a local density analysis technique. The proposed procedure is validated by its application to two architecturally complex, historic brick buildings. Accuracies of at least 86% were achieved, with computational times as little as 0.53 s for detecting features from a data set of 5.0 million points. The accuracy more than rivalled the current state of the art, while being up to six times faster and with the further advantage of requiring no manual intervention or reliance on a priori information. Numéro de notice : A2018-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.004 Date de publication en ligne : 09/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90592
in ISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 134 - 149[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018091 RAB Livre Centre de documentation En réserve L003 Disponible 081-2018093 DEP-EXM Livre LASTIG Dépôt en unité Exclu du prêt 081-2018092 DEP-EAF Livre Nancy Dépôt en unité Exclu du prêt Comparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
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Titre : Comparison of high-density LiDAR and satellite photogrammetry for forest inventory Type de document : Article/Communication Auteurs : Grant D. Pearse, Auteur ; Jonathan P. Dash, Auteur ; Henrik J. Persson, Auteur ; Michael S. Watt, Auteur Année de publication : 2018 Article en page(s) : pp 257 - 267 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] hauteur des arbres
[Termes IGN] image multibande
[Termes IGN] image Pléiades-HR
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Nouvelle-Zélande
[Termes IGN] photogrammétrie numérique
[Termes IGN] Pinus radiata
[Termes IGN] semis de points
[Termes IGN] surface terrière
[Termes IGN] sylviculture
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Point cloud data derived from stereo satellite imagery has the potential to provide large-scale forest inventory assessment but these methods are known to include higher error than airborne laser scanning (ALS). This study compares the accuracy of forest inventory attributes estimated from high-density ALS (21.1 pulses m−2) point cloud data (PCD) and PCD derived from photogrammetric methods applied to stereo satellite imagery obtained over a Pinus radiata D. Don plantation forest in New Zealand. The statistical and textural properties of the canopy height models (CHMs) derived from each point cloud were included alongside standard PCD metrics as a means of improving the accuracy of predictions for key forest inventory attributes. For mean top height (a measure of dominant height in a stand), ALS data produced better estimates (R2 = 0.88; RMSE = 1.7 m) than those obtained from satellite data (R2 = 0.81; RMSE = 2.1 m). This was attributable to a general over-estimation of canopy heights in the satellite PCD. ALS models produced poor estimates of stand density (R2 = 0.48; RMSE = 112.1 stems ha−1), as did the satellite PCD models (R2 = 0.42; RMSE = 118.4 stems ha−1). ALS models produced accurate estimates of basal area (R2 = 0.58; RMSE = 12 m2 ha−1), total stem volume (R2 = 0.72; RMSE = 107.5 m3 ha−1), and total recoverable volume (R2 = 0.74; RMSE = 92.9 m3 ha−1). These values differed little from the estimates of basal area (R2 = 0.57; RMSE = 12.2 m2 ha−1), total stem volume (R2 = 0.70; RMSE = 112.6 m3 ha−1), and total recoverable volume (R2 = 0.73; RMSE = 96 m3 ha−1) obtained from satellite PCD models. The statistical and textural metrics computed from the CHMs were important variables in all of the models derived from both satellite and ALS PCD, nearly always outranking the standard PCD metrics in measures of importance. For the satellite PCD models, the CHM-derived metrics were nearly exclusively identified as important variables. These results clearly show that point cloud data obtained from stereo satellite imagery are useful for prediction of forest inventory attributes in intensively managed forests on steeper terrain. Furthermore, these data offer forest managers the benefit of obtaining both inventory data and high-resolution multispectral imagery from a single product. Numéro de notice : A2018-295 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.006 Date de publication en ligne : 22/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90413
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 257 - 267[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)
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Titre : A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification Type de document : Article/Communication Auteurs : Zhen Wang, Auteur ; Liqiang Zhang, Auteur ; Liang Zhang, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 4594 - 4604 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] arbre aléatoire
[Termes IGN] classification par réseau neuronal
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] méthode robuste
[Termes IGN] Perceptron multicouche
[Termes IGN] pondération
[Termes IGN] précision de la classification
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsMots-clés libres : deep neural network with spatial pooling (DNNSP) Résumé : (Auteur) The large number of object categories and many overlapping or closely neighboring objects in large-scale urban scenes pose great challenges in point cloud classification. Most works in deep learning have achieved a great success on regular input representations, but they are hard to be directly applied to classify point clouds due to the irregularity and inhomogeneity of the data. In this paper, a deep neural network with spatial pooling (DNNSP) is proposed to classify large-scale point clouds without rasterization. The DNNSP first obtains the point-based feature descriptors of all points in each point cluster. The distance minimum spanning tree-based pooling is then applied in the point feature representation to describe the spatial information among the points in the point clusters. The max pooling is next employed to aggregate the point-based features into the cluster-based features. To assure the DNNSP is invariant to the point permutation and sizes of the point clusters, the point-based feature representation is determined by the multilayer perception (MLP) and the weight sharing for each point is retained, which means that the weight of each point in the same layer is the same. In this way, the DNNSP can learn the features of points scaled from the entire regions to the centers of the point clusters, which makes the point cluster-based feature representations robust and discriminative. Finally, the cluster-based features are input to another MLP for point cloud classification. We have evaluated qualitatively and quantitatively the proposed method using several airborne laser scanning and terrestrial laser scanning point cloud data sets. The experimental results have demonstrated the effectiveness of our method in improving classification accuracy. Numéro de notice : A2018-471 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2829625 Date de publication en ligne : 22/05/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2829625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91253
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 8 (August 2018) . - pp 4594 - 4604[article]Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)
PermalinkIncorporating tree- and stand-level information on crown base height into multivariate forest management inventories based on airborne laser scanning / Matti Maltamo in Silva fennica, vol 52 n° 3 ([01/08/2018])
PermalinkSurface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)
PermalinkThe use of geomatic techniques to improve the management of metro infrastructure / Maria Amparo Núñez-Andrés in Survey review, vol 50 n° 362 (August 2018)
PermalinkModélisation 3D de la végétation sur le territoire de Rennes Métropole (Partie 1) / Coralie Leblan in Géomatique expert, n° 123 (juillet - août 2018)
PermalinkAdaptive stopping criterion for top-down segmentation of ALS point clouds in temperate coniferous forests / Nina Amiri in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)
PermalinkDesign and implementation of a 4D Web application for analytical visualization of smart city applications / Syed Monjur Murshed in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)
PermalinkSecond iteration of photogrammetric processing to refine image orientation with improved tie-points / Truong Giang Nguyen in Sensors, vol 18 n° 7 (July 2018)
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PermalinkConstruction control and documentation of facade elements using terrestrial laser scanning / Ján Erdélyi in Applied geomatics, vol 10 n° 2 (June 2018)
PermalinkDepth camera indoor mapping for 3D virtual radio play / Juho-Pekka Virtanen in Photogrammetric record, vol 33 n° 162 (June 2018)
PermalinkGenève 1850, du plan-relief Magnin à la visite virtuelle / David Desbuisson in XYZ, n° 155 (juin - août 2018)
PermalinkLandmark based localization in urban environment / Xiaozhi Qu in ISPRS Journal of photogrammetry and remote sensing, vol 140 (June 2018)
PermalinkModeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data / Manuel Arias-Rodil in Annals of Forest Science, vol 75 n° 2 (June 2018)
PermalinkRange-image: Incorporating sensor topology for lidar point cloud processing / Pierre Biasutti in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)
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PermalinkUsing kites for 3-D mapping of gullies at decimetre-resolution over several square kilometres: a case study on the Kamech catchment, Tunisia / Denis Feurer in Natural Hazards and Earth System Sciences, vol 18 n° 6 ([01/06/2018])
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PermalinkA voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation / Yusheng Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)
PermalinkWeighted simplicial complex reconstruction from mobile laser scanning using sensor topology / Stéphane Guinard in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)
PermalinkLarge scale textured mesh reconstruction from mobile mapping images and LIDAR scans / Mohamed Boussaha in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2 (June 2018)
PermalinkSensor-topology based simplicial complex reconstruction from mobile laser scanning / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2 (June 2018)
PermalinkAccurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information / Yongzhi Wang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
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