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Utilisation de l’apprentissage profond dans la modélisation 3D urbaine : partie 2, post-traitement et évaluation / Hamza Ben Addou in Géomatique expert, n° 136 (novembre - décembre 2021)
[article]
Titre : Utilisation de l’apprentissage profond dans la modélisation 3D urbaine : partie 2, post-traitement et évaluation Type de document : Article/Communication Auteurs : Hamza Ben Addou, Auteur Année de publication : 2021 Article en page(s) : pp 42 -47 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] apprentissage profond
[Termes IGN] CityGML
[Termes IGN] classification automatique d'objets
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] emprise au sol
[Termes IGN] maquette numérique
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique du bâti
[Termes IGN] modélisation 3D
[Termes IGN] niveau de détail
[Termes IGN] orthoimage
[Termes IGN] primitive géométrique
[Termes IGN] toitRésumé : (Auteur) Post-traitement des données issues de l’algorithme d’apprentissage profond et modélisation 3D urbaine automatique Numéro de notice : A2021-919 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/11/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99335
in Géomatique expert > n° 136 (novembre - décembre 2021) . - pp 42 -47[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité IFN-001-P002286 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt A vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)
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Titre : A vector-based method for drainage network analysis based on LiDAR data Type de document : Article/Communication Auteurs : Fangzheng Lyu, Auteur ; Xinlin Ma, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse vectorielle
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] interpolation spatiale
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau hydrographique
[Termes IGN] semis de pointsRésumé : (auteur) Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. Numéro de notice : A2021-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104892 Date de publication en ligne : 24/07/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98733
in Computers & geosciences > vol 156 (November 2021)[article]Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada / Bernadett Dobre in Transactions in GIS, vol 25 n° 5 (October 2021)
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Titre : Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada Type de document : Article/Communication Auteurs : Bernadett Dobre, Auteur ; Istvan P. Kovács, Auteur ; Titusz Bugya, Auteur Année de publication : 2021 Article en page(s) : pp 2262 - 2282 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] bassin hydrographique
[Termes IGN] carte géologique
[Termes IGN] données lidar
[Termes IGN] géomorphologie
[Termes IGN] GRASS
[Termes IGN] MNS ASTER
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de surface
[Termes IGN] Nevada (Etats-Unis)
[Termes IGN] semis de points
[Termes IGN] sommet (relief)
[Termes IGN] zone semi-arideRésumé : (auteur) This article explores the advantages and limitations of open-source digital elevation models (DEMs) generated from various acquisition methods and at various spatial resolutions, through extracting geomorphic surface remnants in a semi-arid, mountainous topographic environment. Even if the tested models have well-known vertical accuracy and precision, their reliability for peak detection is still waiting to be studied. In this research, we investigate peaks as remnants of degraded geomorphic surfaces. Peaks of surface remnants can help to reconstruct geomorphic surfaces and evaluate DEM applicabilities, since they can enhance the identification of overall accuracy. Our methodology uses a well-known open-source GRASS GIS Geomorphons module (r.geomorphon) on several recently released and widely used DEMs covering the Desatoya Mountains study area. We conclude that, despite the characteristic differences in the accuracy of the analyzed DEMs, all of those examined proved to be appropriate to detect surface remnants. Numéro de notice : A2021-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/tgis.12819 Date de publication en ligne : 10/08/2021 En ligne : https://doi.org/10.1111/tgis.12819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99301
in Transactions in GIS > vol 25 n° 5 (October 2021) . - pp 2262 - 2282[article]Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
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Titre : Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests Type de document : Article/Communication Auteurs : Meinrad Abegg, Auteur ; Ruedi Boesch, Auteur ; Michael E. Schaepman, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8153 - 8167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité du peuplement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] faisceau laser
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] qualité des données
[Termes IGN] semis de points
[Termes IGN] signal lidar
[Termes IGN] Suisse
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) In recent years, portable laser scanning devices and their applications in the context of forest mensuration have undergone rapid methodological and technological developments. Devices have become smaller, lighter, and more affordable, whereas new data-driven methods and software packages have facilitated the derivation of information from point clouds. Thus, terrestrial laser scanning (TLS) is now well established, and laser–object interactions have been studied using theoretical, modeling, and experimental approaches. The representation of scanned objects in terms of accuracy and completeness is a key factor for successful feature extraction. Still, little is known about the influence of TLS and survey properties on point clouds in complex scattering environments, such as forests. In this study, we investigate the influence of laser beam diameter and signal triggering on the quality of point clouds in forested environments. Based on the Swiss National Forest Inventory data, we simulate the TLS measurements in 684 virtual forest stands using a 3-D content creation suite. We show that small objects lack sufficient representation in the point cloud and they are further negatively influenced by large laser beam diameters, dense stands, and large distances from the scanning device. We provide simulations that make it possible to derive a rationale for decisions regarding the appropriate choice of TLS device and survey configuration for forest inventories. Numéro de notice : A2021-709 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1109/TGRS.2020.3037763 Date de publication en ligne : 08/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3037763 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98608
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8153 - 8167[article]Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)
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Titre : Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing Type de document : Article/Communication Auteurs : Radhika Ravi, Auteur ; Ayman Habib, Auteur Année de publication : 2021 Article en page(s) : pp 717 - 733 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] alignement des données
[Termes IGN] chevauchement
[Termes IGN] compensation par moindres carrés
[Termes IGN] données lidar
[Termes IGN] lidar mobile
[Termes IGN] matrice
[Termes IGN] matrice de covariance
[Termes IGN] modèle de Gauss-Helmert
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] modèle mathématique
[Termes IGN] modélisation 3D
[Termes IGN] pondération
[Termes IGN] semis de pointsRésumé : (Auteur) This article proposes a solution to special least squares adjustment (LSA) models with a rank-deficient weight matrix, which are commonly encountered in geomatics. The two sources of rank deficiency in weight matrices are discussed: naturally occurring due to the inherent characteristics of LSA mathematical models and artificially induced to eliminate nuisance parameters from LSA estimation. The physical interpretation of the sources of rank deficiency is demonstrated using a case study to solve the problem of 3D line fitting, which is often encountered in geomatics but has not been addressed fully to date. Finally, some geomatics-related applications—mobile lidar system calibration, point cloud registration, and single-photo resection—are discussed along with respective experimental results, to emphasize the need to assess LSA models and their weight matrices to draw inferences regarding the effective contribution of observations. The discussion and results demonstrate the vast applications of this research in geomatics as well as other engineering domains. Numéro de notice : A2021-675 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00081R3 Date de publication en ligne : 10/01/2021 En ligne : https://doi.org/10.14358/PERS.20-00081R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98861
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 717 - 733[article]Réservation
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