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Second iteration of photogrammetric processing to refine image orientation with improved tie-points / Truong Giang Nguyen in Sensors, vol 18 n° 7 (July 2018)
[article]
Titre : Second iteration of photogrammetric processing to refine image orientation with improved tie-points Type de document : Article/Communication Auteurs : Truong Giang Nguyen , Auteur ; Jean-Michaël Muller , Auteur ; Ewelina Rupnik , Auteur ; Christian Thom , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Article en page(s) : n° 2150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage de chambre métrique
[Termes IGN] image captée par drone
[Termes IGN] itération
[Termes IGN] orientation d'image
[Termes IGN] points homologues
[Termes IGN] reconstruction 3D
[Termes IGN] semis de pointsRésumé : (auteur) Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The tie-point extraction step is the opening in the photogrammetric processing chain and therefore plays a key role in the quality of the subsequent image orientation, camera calibration and 3D reconstruction. Improving its precision will have an impact on the obtained 3D. In this research work we describe a method which aims at enhancing the accuracy of image orientation by adding a second iteration photogrammetric processing. The result from the classical processing is used as a priori information to guide the extraction of refined tie-points of better photogrammetric quality. Evaluated on indoor and UAV acquisitions, the proposed methodology shows a significant improvement on the obtained 3D point accuracy. Numéro de notice : A2018-390 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s18072150 Date de publication en ligne : 04/07/2018 En ligne : https://doi.org/10.3390/s18072150 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90807
in Sensors > vol 18 n° 7 (July 2018) . - n° 2150[article]Documents numériques
en open access
Second iteration of photogrammetric processing ... - pdf éditeurAdobe Acrobat PDF Using UAVs for map creation and updating: A case study in Rwanda / Mila Koeva in Survey review, vol 50 n° 361 (July 2018)
[article]
Titre : Using UAVs for map creation and updating: A case study in Rwanda Type de document : Article/Communication Auteurs : Mila Koeva, Auteur ; M. Muneza, Auteur ; Caroline M. Gevaert, Auteur ; Markus Gerke, Auteur ; Francesco Nex, Auteur Année de publication : 2018 Article en page(s) : pp 312 - 325 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] image captée par drone
[Termes IGN] orthophotoplan numérique
[Termes IGN] précision centimétrique
[Termes IGN] Rwanda
[Termes IGN] scène urbaine
[Termes IGN] zone urbaineRésumé : (Auteur) Aerial or satellite images are conventionally used for geospatial data collection. However, unmanned aerial vehicles (UAVs) are emerging as a suitable technology for providing very high spatial and temporal resolution data at a low cost. This paper aims to show the potential of using UAVs for map creation and updating. The whole workflow is introduced in the paper, using a case study in Rwanda, where 954 images were collected with a DJI Phantom 2 Vision Plus quadcopter. An orthophoto covering 0.095 km2 with a spatial resolution of 3.3 cm was produced and used to extract features with a sub-decimetre accuracy. Quantitative and qualitative control of the UAV data products were performed, indicating that the obtained accuracies comply to international standards. Moreover, possible problems and further perspectives were also discussed. The results demonstrate that UAVs provide promising opportunities to create high-resolution and highly accurate orthophotos, thus facilitating map creation and updating. Numéro de notice : A2018-442 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2016.1268756 Date de publication en ligne : 30/12/2016 En ligne : https://doi.org/10.1080/00396265.2016.1268756 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91014
in Survey review > vol 50 n° 361 (July 2018) . - pp 312 - 325[article]Classification of aerial photogrammetric 3D point clouds / Carlos Becker in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 5 (mai 2018)
[article]
Titre : Classification of aerial photogrammetric 3D point clouds Type de document : Article/Communication Auteurs : Carlos Becker, Auteur ; E. Rosinskaya, Auteur ; N. Häni, Auteur ; E. d' Angelo, Auteur ; Christoph Strecha, Auteur Année de publication : 2018 Article en page(s) : pp 287 - 295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] attribut sémantique
[Termes IGN] image aérienne
[Termes IGN] information sémantique
[Termes IGN] modèle numérique de terrain
[Termes IGN] orthoimage
[Termes IGN] Pix4D
[Termes IGN] semis de points
[Termes IGN] valeur radiométriqueRésumé : (Auteur) We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labeling this kind of data is important for tasks such as environmental modeling, object classification, and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on four real-world photogrammetry datasets that were generated with Pix4Dmapper, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than three minutes on a desktop computer. We also demonstrate that our approach can be used to generate accurate Digital Terrain Models, outperforming approaches based on more simple heuristics such as Maximally Stable Extremal Regions. Numéro de notice : A2018-161 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.5.287 Date de publication en ligne : 01/05/2018 En ligne : https://doi.org/10.14358/PERS.84.5.287 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89793
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 5 (mai 2018) . - pp 287 - 295[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas / Bo Wu in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
[article]
Titre : Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Linfu Xie, Auteur ; Han Hu, Auteur ; Qing Zhu, Auteur ; Eric Yau, Auteur Année de publication : 2018 Article en page(s) : pp 119 - 132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] compensation par faisceaux
[Termes IGN] Hong-Kong
[Termes IGN] image aérienne oblique
[Termes IGN] image terrestre
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modélisation 3D
[Termes IGN] Rhénanie du Nord-Wesphalie (Allemagne)
[Termes IGN] zone urbaineRésumé : (Auteur) Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas. Numéro de notice : A2018-112 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89542
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 119 - 132[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Mapping forest characteristics at fine resolution across large landscapes of the southeastern united states using NAIP imagery and FIA field plot data / John Hogland in ISPRS International journal of geo-information, vol 7 n° 4 (April 2018)
[article]
Titre : Mapping forest characteristics at fine resolution across large landscapes of the southeastern united states using NAIP imagery and FIA field plot data Type de document : Article/Communication Auteurs : John Hogland, Auteur ; Nathaniel Anderson, Auteur ; Joseph St. Peter, Auteur ; Jason Drake, Auteur ; Paul Medley, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] composition floristique
[Termes IGN] densité du bois
[Termes IGN] Etats-Unis
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Pinus (genre)
[Termes IGN] surface terrière
[Termes IGN] télédétection aérienne
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Accurate information is important for effective management of natural resources. In the field of forestry, field measurements of forest characteristics such as species composition, basal area, and stand density are used to inform and evaluate management activities. Quantifying these metrics accurately across large landscapes in a meaningful way is extremely important to facilitate informed decision-making. In this study, we present a remote sensing based methodology to estimate species composition, basal area and stand tree density for pine and hardwood tree species at the spatial resolution of a Forest Inventory Analysis (FIA) program plot (78 m by 70 m). Our methodology uses textural metrics derived at this spatial scale to relate plot summaries of forest characteristics to remotely sensed National Agricultural Imagery Program (NAIP) aerial imagery across broad extents. Our findings quantify strong relationships between NAIP imagery and FIA field data. On average, models of basal area and trees per acre accounted for 43% of the variation in the FIA data, while models identifying species composition had less than 15.2% error in predicted class probabilities. Moreover, these relationships can be used to spatially characterize the condition of forests at fine spatial resolutions across broad extents. Numéro de notice : A2018-109 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7040140 En ligne : https://doi.org/10.3390/ijgi7040140 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89538
in ISPRS International journal of geo-information > vol 7 n° 4 (April 2018)[article]Comparing nearest neighbor configurations in the prediction of species-specific diameter distributions / Janne Raty in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkContextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)PermalinkImage classification-based ground filtering of point clouds extracted from UAV-based aerial photos / Volkan Yilmaz in Geocarto international, vol 33 n° 3 (March 2018)PermalinkLRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkValue of airborne laser scanning and digital aerial photogrammetry data in forest decision making / Annika S. Kangas in Silva fennica, vol 52 n° 1 ([01/02/2018])PermalinkActive learning-based optimized training library generation for object-oriented image classification / Rajeswari Balasubramaniam in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkChaîne de traitement de photogrammétrie en vue de réaliser un MNS à partir de photographies aériennes / Alice Gonnaud (2018)PermalinkPermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkDéveloppement d'un outil de manipulation optimisée de rasters volumineux / Amaury Zarzelli (2018)Permalink