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Forest structural complexity tool: An open source, fully-automated tool for measuring forest point clouds / Sean Krisanski in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4677 Titre : Forest structural complexity tool: An open source, fully-automated tool for measuring forest point clouds Type de document : Article/Communication Auteurs : Sean Krisanski, Auteur ; Mohammad Sadegh Taskhiri, Auteur ; Susana Gonzalez Aracil, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4677 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] édition en libre accès [Termes IGN] logiciel libre [Termes IGN] modèle numérique de terrain [Termes IGN] Python (langage de programmation) [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] squelettisation [Termes IGN] structure-from-motion [Termes IGN] télédétection par lidar Résumé : (auteur) Forest mensuration remains critical in managing our forests sustainably, however, capturing such measurements remains costly, time-consuming and provides minimal amounts of information such as diameter at breast height (DBH), location, and height. Plot scale remote sensing techniques show great promise in extracting detailed forest measurements rapidly and cheaply, however, they have been held back from large-scale implementation due to the complex and time-consuming workflows required to utilize them. This work is focused on describing and evaluating an approach to create a robust, sensor-agnostic and fully automated forest point cloud measurement tool called the Forest Structural Complexity Tool (FSCT). The performance of FSCT is evaluated using 49 forest plots of terrestrial laser scanned (TLS) point clouds and 7022 destructively sampled manual diameter measurements of the stems. FSCT was able to match 5141 of the reference diameter measurements fully automatically with mean, median and root mean squared errors (RMSE) of 0.032 m, 0.02 m, and 0.103 m respectively. A video demonstration is also provided to qualitatively demonstrate the diversity of point cloud datasets that the tool is capable of measuring. FSCT is provided as open source, with the goal of enabling plot scale remote sensing techniques to replace most structural forest mensuration in research and industry. Future work on this project will seek to make incremental improvements to this methodology to further improve the reliability and accuracy of this tool in most high-resolution forest point clouds. Numéro de notice : A2021-861 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : https://doi.org/10.3390/rs13224677 Date de publication en ligne : 19/11/2021 En ligne : https://doi.org/10.3390/rs13224677 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99075 [article]

Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods / Ferdinand Maiwald in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 748 Titre : Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods Type de document : Article/Communication Auteurs : Ferdinand Maiwald, Auteur ; Christoph Lehmann, Auteur ; Taras Lazariv, Auteur Année de publication : 2021 Article en page(s) : n° 748 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] apprentissage automatique [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] échelle de temps [Termes IGN] estimation de pose [Termes IGN] image ancienne [Termes IGN] image terrestre [Termes IGN] métadonnées [Termes IGN] modélisation 4D [Termes IGN] patrimoine culturel [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] récupération de données [Termes IGN] structure-from-motion [Termes IGN] système d'information géographique Résumé : (auteur) The idea of virtual time machines in digital environments like hand-held virtual reality or four-dimensional (4D) geographic information systems requires an accurate positioning and orientation of urban historical images. The browsing of large repositories to retrieve historical images and their subsequent precise pose estimation is still a manual and time-consuming process in the field of Cultural Heritage. This contribution presents an end-to-end pipeline from finding relevant images with utilization of content-based image retrieval to photogrammetric pose estimation of large historical terrestrial image datasets. Image retrieval as well as pose estimation are challenging tasks and are subjects of current research. Thereby, research has a strong focus on contemporary images but the methods are not considered for a use on historical image material. The first part of the pipeline comprises the precise selection of many relevant historical images based on a few example images (so called query images) by using content-based image retrieval. Therefore, two different retrieval approaches based on convolutional neural networks (CNN) are tested, evaluated, and compared with conventional metadata search in repositories. Results show that image retrieval approaches outperform the metadata search and are a valuable strategy for finding images of interest. The second part of the pipeline uses techniques of photogrammetry to derive the camera position and orientation of the historical images identified by the image retrieval. Multiple feature matching methods are used on four different datasets, the scene is reconstructed in the Structure-from-Motion software COLMAP, and all experiments are evaluated on a newly generated historical benchmark dataset. A large number of oriented images, as well as low error measures for most of the datasets, show that the workflow can be successfully applied. Finally, the combination of a CNN-based image retrieval and the feature matching methods SuperGlue and DISK show very promising results to realize a fully automated workflow. Such an automated workflow of selection and pose estimation of historical terrestrial images enables the creation of large-scale 4D models. Numéro de notice : A2021-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110748 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.3390/ijgi10110748 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98964 [article]

Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 ([02/11/2021])  

Public [article]  inJournal of maps > vol 17 n° 4 [02/11/2021] . - pp 241 - 252 Titre : Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques Type de document : Article/Communication Auteurs : Peter G. Chirico, Auteur ; Sarah E. Bergstresser, Auteur ; Jessica D. DeWitt, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 241 - 252 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] aménagement du territoire [Termes IGN] archives [Termes IGN] bassin hydrographique [Termes IGN] cartographie géomorphologique [Termes IGN] croissance urbaine [Termes IGN] détection de changement [Termes IGN] érosion anthropique [Termes IGN] modèle numérique de surface [Termes IGN] modélisation spatiale [Termes IGN] photogrammétrie numérique [Termes IGN] photographie aérienne [Termes IGN] structure-from-motion [Termes IGN] Virginie (Etats-Unis) Résumé : (auteur) Increasing urbanization and suburban growth in cities globally has highlighted the importance of land planning using detailed geomorphologic maps that depict anthropogenic landform changes. Such mapping provides information crucial for land management, hazard identification, and the management of the challenges arising from urbanization. The development and use of quantitative and repeatable methods to map anthropogenic and natural processes are required to advance the science of urban geomorphological mapping. This study investigated the application of geospatial modeling, structure-from-motion (SfM) photogrammetric methods and DEM differencing as means of quantifying anthropogenic landform changes from archival aerial imagery. Anthropogenic landforms were incorporated into a detailed geomorphologic map in an urbanizing watershed located in the Washington, D.C. metropolitan suburb of Vienna, Virginia. Numéro de notice : A2021-813 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1080/17445647.2020.1746419 Date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1080/17445647.2020.1746419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98887 [article]

Accuracy assessment of RTK-GNSS equipped UAV conducted as-built surveys for construction site modelling / Sander Varbla in Survey review, Vol 53 n° 381 (November 2021)  

Public [article]  inSurvey review > Vol 53 n° 381 (November 2021) . - pp 477 - 492 Titre : Accuracy assessment of RTK-GNSS equipped UAV conducted as-built surveys for construction site modelling Type de document : Article/Communication Auteurs : Sander Varbla, Auteur ; Raido Puust, Auteur ; Artu Ellmann, Auteur Année de publication : 2021 Article en page(s) : pp 477 - 492 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données localisées 3D [Termes IGN] géoréférencement direct [Termes IGN] image captée par drone [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] photogrammétrie aérienne [Termes IGN] point d'appui [Termes IGN] positionnement cinématique en temps réel [Termes IGN] précision centimétrique [Termes IGN] structure-from-motion Résumé : (Auteur) Regular as-built surveys have become a necessary input for building information modelling. Such large-scale 3D data capturing can be conducted effectively by combining structure-from-motion and unmanned aerial vehicles (UAV). Using a RTK-GNSS equipped UAV, 22 repeated weekly campaigns were conducted at two altitudes in various conditions. The photogrammetric approach yielded 3D models, which were compared to the terrestrial laser scanning based ground truth. Better than 2.8 cm geometry RMSE was consistently achieved using integrated georeferencing. It is concluded that the RTK-GNSS based georeferencing enables reaching better than 5 cm geometry accuracy by utilising at least one ground control point. Numéro de notice : A2021-912 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1830544 Date de publication en ligne : 15/10/2020 En ligne : https://doi.org/10.1080/00396265.2020.1830544 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99310 [article]

Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features / Bai Zhu in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 181 (November 2021) . - pp 129 - 147 Titre : Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features Type de document : Article/Communication Auteurs : Bai Zhu, Auteur ; Yuanxin Ye, Auteur ; Liang Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 129 - 147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme ICP [Termes IGN] correction géométrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] élément d'orientation externe [Termes IGN] enregistrement de données [Termes IGN] filtre de Gabor [Termes IGN] image aérienne [Termes IGN] recalage d'image [Termes IGN] semis de points [Termes IGN] SIFT (algorithme) [Termes IGN] structure-from-motion Résumé : (auteur) Co-registration of aerial imagery and Light Detection and Ranging (LiDAR) data is quite challenging because the different imaging mechanisms produce significant geometric and radiometric distortions between the two multimodal data sources. To address this problem, we propose a robust and effective coarse-to-fine registration method that is conducted in two stages utilizing spatial constraints and Gabor structural features. In the first stage, the LiDAR point cloud data is transformed into an intensity map that is used as the reference image. Then, coarse registration is completed by designing a partition-based Features from Accelerated Segment Test (FAST) operator to extract the uniformly distributed interest points in the aerial images and thereafter performing a local geometric correction based on the collinearity equations using the exterior orientation parameters (EoPs). The coarse registration aims to provide a reliable spatial geometry relationship for the subsequent fine registration and is designed to eliminate rotation and scale changes, as well as making only a few translation differences exist between the images. In the second stage, a novel feature descriptor called multi-Scale and multi-Directional Features of odd Gabor (SDFG) is first built to capture the multi-scale and multi-directional structural properties of the images. Then, the three-dimensional (3D) phase correlation (PC) of the SDFG descriptor is established to detect the control points (CPs) between the aerial and LiDAR intensity image in the frequency domain, where the image matching is accelerated by the 3D Fast Fourier Transform (FFT) technique. Finally, the obtained CPs not only are employed to refine the EoPs, but also are used to achieve the fine registration of the aerial images and LiDAR data. We conduct experiments to verify the robustness of the proposed registration method using three sets of aerial images and LiDAR data with different scene coverage. Experimental results show that the proposed method is robust to geometric distortions and radiometric changes. Moreover, it achieves the registration accuracy of less than 2 pixels for all cases, which outperforms the current four state-of-the-art methods, demonstrating its superior registration performance. Numéro de notice : A2021-773 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.09.010 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98830 [article]

Aerial and UAV images for photogrammetric analysis of Belvedere Glacier evolution in the period 1977–2019 / Carlo Lapige De Gaetani in Remote sensing, vol 13 n° 18 (September-2 2021)  

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Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)  

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Determining optimal photogrammetric adjustment of images obtained from a fixed-wing UAV / Karolina Pargiela in Photogrammetric record, Vol 36 n° 175 (September 2021)  

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Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands / Karel Kuželka in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)  

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An automatic workflow for orientation of historical images with large radiometric and geometric differences / Ferdinand Maiwald in Photogrammetric record, vol 36 n° 174 (June 2021)  

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Automated calibration of smartphone cameras for 3D reconstruction of mechanical pipes / Reza Maalek in Photogrammetric record, vol 36 n° 174 (June 2021)  

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Digital terrain models generated with low-cost UAV photogrammetry: Methodology and accuracy / Sergio Jiménez-Jiménez in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)  

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

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Automated registration of SfM‐MVS multitemporal datasets using terrestrial and oblique aerial images / Luigi Parente in Photogrammetric record, vol 36 n° 173 (March 2021)  

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Robust and fast global image orientation / Xin Wang (2021)  

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