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A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations / Irfan A. Iqbal in Remote sensing, vol 13 n° 17 (September-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 17 (September-1 2021) . - n° 3536 Titre : A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations Type de document : Article/Communication Auteurs : Irfan A. Iqbal, Auteur ; Jon Osborn, Auteur ; Christine Stone, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 3536 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] arbre isolé [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] photogrammétrie aérienne [Termes IGN] photographie aérienne [Termes IGN] Pinus radiata [Termes IGN] semis de points [Termes IGN] Tasmanie [Termes IGN] télémétrie laser aéroporté Numéro de notice : A2021-689 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13173536 date de publication en ligne : 06/09/2021 En ligne : https://doi.org/10.3390/rs13173536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98425 [article]

Three-dimensional reconstruction of single input image based on point cloud / Yu Hou in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 7 (July 2021) . - pp 479 - 484 Titre : Three-dimensional reconstruction of single input image based on point cloud Type de document : Article/Communication Auteurs : Yu Hou, Auteur ; Ruifeng Zhai, Auteur ; Xueyan Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 479 - 484 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage profond [Termes IGN] balayage laser [Termes IGN] classification par réseau neuronal [Termes IGN] données localisées 3D [Termes IGN] jeu de données localisées [Termes IGN] navigation autonome [Termes IGN] réalité virtuelle [Termes IGN] reconstruction 3D [Termes IGN] semis de points Résumé : (Auteur) Three-dimensional reconstruction from a single image has excellent future prospects. The use of neural networks for three-dimensional reconstruction has achieved remarkable results. Most of the current point-cloud-based three-dimensional reconstruction networks are trained using nonreal data sets and do not have good generalizability. Based on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago ()data set of large-scale scenes, this article proposes a method for processing real data sets. The data set produced in this work can better train our network model and realize point cloud reconstruction based on a single picture of the real world. Finally, the constructed point cloud data correspond well to the corresponding three-dimensional shapes, and to a certain extent, the disadvantage of the uneven distribution of the point cloud data obtained by light detection and ranging scanning is overcome using the proposed method. Numéro de notice : A2021-570 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.7.479 date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.14358/PERS.87.7.479 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98162 [article]

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An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 2 (June 2021) . - Article 32 Titre : An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data Type de document : Article/Communication Auteurs : Van-Tho Nguyen, Auteur ; Thiéry Constant, Auteur ; Francis Colin, Auteur Année de publication : 2021 Article en page(s) : Article 32 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] détection d'anomalie [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écorce [Termes IGN] Fagus sylvatica [Termes IGN] qualité du bois [Termes IGN] Quercus sessiliflora [Termes IGN] segmentation d'image [Termes IGN] télémétrie laser terrestre [Termes IGN] tronc Résumé : (Auteur) We designed a novel method allowing to automatically detect and measure defects on the surface of trunks including branches, branch scars, and epicormics from terrestrial LiDAR data by using only high-density 3D information. We could automatically detect and measure the defects with a diameter as small as 0.5 cm on either oak (Quercus petraea (Matt.) Liebl.) or beech (Fagus sylvatica L.) trees that display either rough or smooth bark. Context : Ground-based light detection and ranging (LiDAR) technology describes standing trees with a high level of detail. This provides an opportunity to assess standing tree quality and to use this information in forest inventory. Assuming the availability of a very high level of detail, we could extract information about the surface defects, mainly inherited from past ramification and having a strong impact on wood quality. Aims : Within the general framework of the development of a computing method able to detect, identify, and quantify the defects on the trunk surface described from 3D data produced by a terrestrial LiDAR, this study focuses on the relevance of the whole process for two tree species with contrasted bark roughness (Quercus petraea (Matt.) Liebl. and Fagus sylvatica L.) in terms of detection, identification of the defects, and comparison with measurements performed manually on the bark surface. Methods : First, a segmentation algorithm detected singularities on the trunk surface. Next, a Random Forests machine learning algorithm identified the most probable defect type and allowed the elimination of false detections. Finally, we estimated the position, horizontal, and vertical dimensions of each defect from 3D data, and we compared them to those observed directly on the trunk by an operator. Results : The defects were detected and classified with a high accuracy with an average F1 score (harmonic mean of precision and recall) of 0.74. There were differences in computed and observed defect areas, but a much closer agreement for the number of defects. Conclusion : The information about the defects present on the trunk surface measured from terrestrial LiDAR data can be used in an automated procedure for grading standing trees or roundwoods. Numéro de notice : A2021-326 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01022-3 date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.1007/s13595-020-01022-3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97484 [article]

Geometric calibration of satellite laser altimeters based on waveform matching / Shaoning Li in Photogrammetric record, vol 36 n° 174 (June 2021)  

Public [article]  inPhotogrammetric record > vol 36 n° 174 (June 2021) . - pp 104 - 123 Titre : Geometric calibration of satellite laser altimeters based on waveform matching Type de document : Article/Communication Auteurs : Shaoning Li, Auteur ; Chaokui Li, Auteur ; Guo Zhang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 104 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] données IceSat-Glas [Termes IGN] étalonnage géométrique [Termes IGN] forme d'onde pleine [Termes IGN] Geoscience Laser Altimeter System [Termes IGN] lidar à retour d'onde complète [Termes IGN] modèle numérique de surface [Termes IGN] point d'appui [Termes IGN] précision altimétrique [Termes IGN] signal laser [Termes IGN] télémétrie laser Résumé : (auteur) This study proposes a new geometric calibration method for satellite laser altimeters based on waveform matching to solve the problems of poor initial pointing accuracy and a lack of control data. This non-real-time method obtains ground control points without a fixed calibration field. First, a large area with stepped surfaces is chosen from the laser altimetry coverage. Then, the laser echo waveforms are simulated using digital surface model (DSM) data of the stepped features. The real echo waveform attempts to match the simulated echo waveforms through a waveform matching model using a global constraint. Next, the control points of the laser altimeter are obtained through waveform matching. Finally, a geometric calibration model for laser altimeters is proposed to compensate for laser pointing and ranging errors. Two experiments were conducted to verify the calibration method using ICESat/GLAS data and airborne large-footprint laser data. Experimental results confirm that the method is feasible and results in an improvement in the elevation accuracy for the airborne altimeter from 2 to 0.5 m. Numéro de notice : A2021-473 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12362 date de publication en ligne : 07/05/2021 En ligne : https://doi.org/10.1111/phor.12362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97926 [article]

Validating geoid models with marine GNSS measurements, sea surface models, and additional gravity observations in the Gulf of Finland / Timo Saari in Marine geodesy, vol 44 n° 3 (May 2021)  

Public [article]  inMarine geodesy > vol 44 n° 3 (May 2021) . - pp 196 - 214 Titre : Validating geoid models with marine GNSS measurements, sea surface models, and additional gravity observations in the Gulf of Finland Type de document : Article/Communication Auteurs : Timo Saari, Auteur ; Mirjam Bilker-Koivula, Auteur ; Hannu Koivula, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 196 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] Finlande [Termes IGN] géodésie marine [Termes IGN] geoïde marin [Termes IGN] hauteur ellipsoïdale [Termes IGN] mesurage par GNSS [Termes IGN] modèle de géopotentiel [Termes IGN] nivellement [Termes IGN] surface de la mer Résumé : (auteur) Traditionally, geoid models have been validated using GNSS-levelling benchmarks on land only. As such benchmarks cannot be established offshore, marine areas of geoid models must be evaluated in a different way. In this research, we present a marine GNSS/gravity campaign where existing geoid models were validated at sea areas by GNSS measurements in combination with sea surface models. Additionally, a new geoid model, calculated using the newly collected marine gravity data, was validated. The campaign was carried out with the marine geology research catamaran Geomari (operated by the Geological Survey of Finland), which sailed back and forth the eastern part of the Finnish territorial waters of the Gulf of Finland during the early summer of 2018. From the GNSS and sea surface data we were able to obtain geoid heights at sea areas with an accuracy of a few centimetres. When the GNSS derived geoid heights are compared with geoid heights from the geoid models differences between the respective models are seen in the most eastern and southern parts of the campaign area. The new gravity data changed the geoid model heights by up to 15 cm in areas of sparse/non-existing gravity data. Numéro de notice : A2021-387 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2021.1889727 date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1080/01490419.2021.1889727 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97670 [article]

Horizontal calibration of vessels with UASs / Casey O'Heran in Marine geodesy, vol 44 n° 2 (March 2021)  

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Development of German-Ukrainian cooperations for education and research in photogrammetry and laser scanning / Thomas Luhmann in Geo-spatial Information Science, vol 24 n° 1 (March 2021)  

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Enhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)  

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Le nivellement par GNSS chez SNCF Réseau / Antoine Beuvain Pacheco in XYZ, n° 166 (mars 2021)

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Determination of the under water position of objects by reflectorless total stations / Štefan Rákay in Survey review, vol 53 n°376 (January 2021)  

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Traitements et acquisitions de données lasergrammétriques, topométriques et topographiques / Théo Paille (2021) 

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A decade of modern bridge monitoring using terrestrial laser scanning: Review and future directions / Maria Rashidi in Remote sensing, vol 12 n° 22 (December 2020)  

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Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest / Luka Jurjević in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

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Comparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)  

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Compensation of geometric parameter errors for terrestrial laser scanner by integrating intensity correction / Wanli Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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