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Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)  

Public [article]  inSurvey review > vol 54 n° 385 (July 2022) . - pp 363 - 374 Titre : Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners Type de document : Article/Communication Auteurs : Artu Ellmann, Auteur ; Kaia Kütimets, Auteur ; Sander Varbla, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 363 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arpentage [Termes IGN] cartographie et localisation simultanées [Termes IGN] données lidar [Termes IGN] Estonie [Termes IGN] géoréférencement [Termes IGN] industrie minière [Termes IGN] mine [Termes IGN] modélisation 3D [Termes IGN] schiste [Termes IGN] semis de points [Termes IGN] système de numérisation mobile [Termes IGN] télémètre laser terrestre Résumé : (auteur) Applicability of SLAM (simultaneous localization and mapping) technology for mine surveys and subsequent 3D modelling of post-extracted surfaces is assessed. The resulting surface geometry is validated via terrestrial laser scanner (TLS) acquired reference data. Typical discrepancies remained within 2 and 5 cm in horizontal and vertical directions, respectively. Discrepancies between TLS, SLAM-enabled handheld scanner and conventional surveying results are small and fully satisfy the contemporary accuracy requirements, yet evidence that the conventional mine survey results are affected by the subjectivity of the surveyors. The SLAM-enabled laser scanning hence appears to be the most suitable method for underground mining surveys. Numéro de notice : A2022-537 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1944545 Date de publication en ligne : 07/07/2021 En ligne : https://doi.org/10.1080/00396265.2021.1944545 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101093 [article]

Integration of GNSS observations with volunteered geographic information for improved navigation performance / Tarek Hassan in Journal of applied geodesy, vol 16 n° 3 (July 2022)  

Public [article]  inJournal of applied geodesy > vol 16 n° 3 (July 2022) . - pp 265 - 277 Titre : Integration of GNSS observations with volunteered geographic information for improved navigation performance Type de document : Article/Communication Auteurs : Tarek Hassan, Auteur ; Tamer Fath-Allah, Auteur ; Mohamed Elhabiby, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 265 - 277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données GNSS [Termes IGN] données localisées des bénévoles [Termes IGN] Google Earth [Termes IGN] hauteur du bâti [Termes IGN] modélisation 3D [Termes IGN] OpenStreetMap [Termes IGN] positionnement par GNSS [Termes IGN] signal GNSS [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) Pedestrian and vehicular navigation relies mainly on Global Navigation Satellite System (GNSS). Even if different navigation systems are integrated, GNSS positioning remains the core of any navigation process as it is the only system capable of providing independent solutions. However, in harsh environments, especially urban ones, GNSS signals are confronted by many obstructions causing the satellite signals to reach the receivers through reflected paths. These No-Line of Sight (NLOS) signals can affect the positioning accuracy significantly. This contribution proposes a new algorithm to detect and exclude these NLOS signals using 3D building models constructed from Volunteered Geographic Information (VGI). OpenStreetMap (OSM) and Google Earth (GE) data are combined to build the 3D models incorporated with GNSS signals in the algorithm. Real field data are used for testing and validation of the presented algorithm and strategy. The accuracy improvement, after exclusion of the NLOS signals, is evaluated employing phase-smoothed code observations. The results show that applying the proposed algorithm can improve the horizontal positioning accuracy remarkably. This improvement reaches 10.72 m, and the Root Mean Square Error (RMSE) drops by 1.64 m (46 % improvement) throughout the epochs with detected NLOS satellites. In addition, the improvement is analyzed in the Along-Track (AT) and Cross-Track (CT) directions. It reaches 6.89 m in the AT direction with a drop of 1.076 m in the RMSE value, while it reaches 8.64 m with a drop of 1.239 m in the RMSE value in the CT direction. Numéro de notice : A2022-496 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0063 Date de publication en ligne : 23/03/2022 En ligne : https://doi.org/10.1515/jag-2021-0063 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100986 [article]

Simulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading / Štefan Kohek in International journal of applied Earth observation and geoinformation, vol 111 (July 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 111 (July 2022) . - n° 102844 Titre : Simulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading Type de document : Article/Communication Auteurs : Štefan Kohek, Auteur ; Borut Žalik, Auteur ; Damjan Strnad, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102844 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse de sensibilité [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] dissymétrie [Termes IGN] données lidar [Termes IGN] données topographiques [Termes IGN] houppier [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] modèle numérique de terrain [Termes IGN] modélisation 3D [Termes IGN] modélisation de la forêt [Termes IGN] ombre [Termes IGN] semis de points [Termes IGN] Slovénie Résumé : (auteur) Reliable forest growth forecasting requires detailed tree data for forest simulation, while manual on-site collection of relevant data is work-intensive and unfeasible in larger forests. This paper proposes a complete methodology for fully automated forest growth simulation that relies primarily on airborne topographic Light Detection And Ranging (LiDAR) point clouds of individual trees. The proposed method estimates tree parameters and performs growth of individual trees based on an individual-based forest growth simulator, named BWINPro. In addition, competition and detailed asymmetric tree crown growth are modeled regarding the shading of tree crowns, which is estimated from the surrounding environment and neighbor trees. The result of the proposed approach is a new point cloud for subsequent analyses. The proposed method was validated by comparing canopy height models derived from the point clouds of the simulated trees with canopy height models derived from more recent ground truth point clouds. The results demonstrate the efficacy of the proposed method which achieves a 9.4% higher accuracy than the averaged linear regression model and, in the case of datasets with more distinct self-standing trees, where a tree crown boundary plays major role, a 4.1% higher accuracy than the directly fitted linear regression model. Numéro de notice : A2022-552 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102844 Date de publication en ligne : 04/06/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102844 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101156 [article]

3D modeling method for dome structure using digital geological map and DEM / Xian-Yu Liu in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 339 Titre : 3D modeling method for dome structure using digital geological map and DEM Type de document : Article/Communication Auteurs : Xian-Yu Liu, Auteur ; An-Bo Li, Auteur ; Hao Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 339 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] carte géologique [Termes IGN] carte stratigraphique [Termes IGN] courbe de Bézier [Termes IGN] modèle géologique [Termes IGN] modèle numérique de surface [Termes IGN] modélisation 3D [Termes IGN] structure géologique Résumé : (auteur) Geological maps have wide coverage with low acquisition difficulty. When other geological survey data are scarce, they are a valuable source of geological structure information for geological modeling. However, for structures with large deformation, geological map information has difficulty meeting the requirement of its 3D geological modeling. Therefore, this paper takes the dome structure as an example to explore a 3D modeling method based on geological maps, DEM and related geological knowledge. The method includes: (1) adaptively calculating the attitude of points on the stratigraphic boundaries; (2) inferring and generating the bottom boundary of the model from the attitude data of the boundary points; (3) generating the model interface constrained by Bézier curves based on the bottom boundary; (4) generating the top and bottom surfaces of the stratum; and (5) stitching each surface of the geological body to generate the final dome model. Case studies of the dome in Wulongshan in China and the Richat structure in Mauritania show that this method can build a solid model of the dome based only on geological maps and DEM data, whose morphological features are basically consistent with those embodied in the section view or the model generated by traditional methods. Numéro de notice : A2022-482 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11060339 Date de publication en ligne : 07/06/2022 En ligne : https://doi.org/10.3390/ijgi11060339 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100895 [article]

Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification / Yongqiang Mao in ISPRS Journal of photogrammetry and remote sensing, vol 188 (June 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 188 (June 2022) . - pp 45 - 61 Titre : Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification Type de document : Article/Communication Auteurs : Yongqiang Mao, Auteur ; Kaiqiang chen, Auteur ; Wenhui Diao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 45 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage automatique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données laser [Termes IGN] données localisées 3D [Termes IGN] Perceptron multicouche [Termes IGN] représentation parcimonieuse [Termes IGN] réseau neuronal de graphes [Termes IGN] semis de points [Termes IGN] stratification de données [Termes IGN] voxel Résumé : (Auteur) The classification of airborne laser scanning (ALS) point clouds is a critical task of remote sensing and photogrammetry fields. Although recent deep learning-based methods have achieved satisfactory performance, they have ignored the unicity of the receptive field, which makes the ALS point cloud classification remain challenging for the distinguishment of the areas with complex structures and extreme scale variations. In this article, for the objective of configuring multi-receptive field features, we propose a novel receptive field fusion-and-stratification network (RFFS-Net). With a novel dilated graph convolution (DGConv) and its extension annular dilated convolution (ADConv) as basic building blocks, the receptive field fusion process is implemented with the dilated and annular graph fusion (DAGFusion) module, which obtains multi-receptive field feature representation through capturing dilated and annular graphs with various receptive regions. The stratification of the receptive fields with point sets of different resolutions as the calculation bases is performed with Multi-level Decoders nested in RFFS-Net and driven by the multi-level receptive field aggregation loss (MRFALoss) to drive the network to learn in the direction of the supervision labels with different resolutions. With receptive field fusion-and-stratification, RFFS-Net is more adaptable to the classification of regions with complex structures and extreme scale variations in large-scale ALS point clouds. Evaluated on the ISPRS Vaihingen 3D dataset, our RFFS-Net significantly outperforms the baseline (i.e. PointConv) approach by 5.3% on mF1 and 5.4% on mIoU, accomplishing an overall accuracy of 82.1%, an mF1 of 71.6%, and an mIoU of 58.2%. The experiments show that our RFFS-Net achieves a new state-of-the-art classification performance on powerline, car, and fence classes. Furthermore, experiments on the LASDU dataset and the 2019 IEEE-GRSS Data Fusion Contest dataset show that RFFS-Net achieves a new state-of-the-art classification performance. The code is available at github.com/WingkeungM/RFFS-Net. Numéro de notice : A2022-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.03.019 Date de publication en ligne : 07/04/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.03.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100532 [article]

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Exploring digital twin adaptation to the urban environment: comparison with CIM to avoid silo-based approaches / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)  

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Projective multitexturing of current 3D city models and point clouds with many historical images / Maria Scarlleth Gomes de Castro in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)  

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A voxel-based method for the three-dimensional modelling of heathland from lidar point clouds: first results / N. Homainejad in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)  

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Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure / Xinxin Wu in Sustainable Cities and Society, vol 80 (May 2022)  

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High-performance adaptive texture streaming and rendering of large 3D cities / Alex Zhang in The Visual Computer, vol 38 n° 4 (April 2022)  

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Automated 3D reconstruction of LoD2 and LoD1 models for All 10 million buildings of the Netherlands / Ravi Peters in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)  

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A cost-effective method for reconstructing city-building 3D models from sparse Lidar point clouds / Marek Kulawiak in Remote sensing, vol 14 n° 5 (March-1 2022)  

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Evaluating the 3D integrity of underwater structure from motion workflows / Ian M. Lochhead in Photogrammetric record, vol 37 n° 177 (March 2022)  

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Raw GIS to 3D road modeling for real-time traffic simulation / Yacine Amara in The Visual Computer, vol 38 n° 1 (January 2022)  

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3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)  

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