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Towards online UAS‐based photogrammetric measurements for 3D metrology inspection / Fabio Menna in Photogrammetric record, vol 35 n° 172 (December 2020)
[article]
Titre : Towards online UAS‐based photogrammetric measurements for 3D metrology inspection Type de document : Article/Communication Auteurs : Fabio Menna, Auteur ; Erica Nocerino, Auteur ; Fabio Remondino, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 467 - 486 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] antenne
[Termes IGN] caméra 3D temps-de-vol
[Termes IGN] caméra numérique
[Termes IGN] image captée par drone
[Termes IGN] métrologie
[Termes IGN] photogrammétrie aérienne
[Termes IGN] plan de vol
[Termes IGN] positionnement cinématique en temps réelRésumé : (auteur) This paper presents the development of a vision metrology system for high‐accuracy three‐dimensional measurements of large structures requiring dimensional tolerancing. The proposed system integrates a V‐STARS N platinum photogrammetric system from Geodetic Systems, a DJI M600 Pro UAS with Ronin‐MX gimbal and a dual antenna for real‐time kinematic positioning. The paper presents the system architecture and the developed software for camera network simulation and image acquisition. As an acquisition scenario, a large dish parabolic antenna is simulated. The benefits of the developed procedure include the ability to handle obstacle avoidance and self‐occlusions and, employing a rigorous camera network simulation approach, to overcome the limitations of currently available flight planning commercial tools that are mainly conceived for mapping applications. Future work will consider extensive testing of the platform in real‐case scenarios. Numéro de notice : A2020-799 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12338 Date de publication en ligne : 18/11/2020 En ligne : https://doi.org/10.1111/phor.12338 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96720
in Photogrammetric record > vol 35 n° 172 (December 2020) . - pp 467 - 486[article]Use of remote sensing data to improve the efficiency of National Forest Inventories: A case study from the United States National Forest Inventory / Andrew J. Lister in Forests, vol 11 n° 12 (December 2020)
[article]
Titre : Use of remote sensing data to improve the efficiency of National Forest Inventories: A case study from the United States National Forest Inventory Type de document : Article/Communication Auteurs : Andrew J. Lister, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 1364 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] échantillonnage
[Termes IGN] Etats-Unis
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] surveillance forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Globally, forests are a crucial natural resource, and their sound management is critical for human and ecosystem health and well-being. Efforts to manage forests depend upon reliable data on the status of and trends in forest resources. When these data come from well-designed natural resource monitoring (NRM) systems, decision makers can make science-informed decisions. National forest inventories (NFIs) are a cornerstone of NRM systems, but require capacity and skills to implement. Efficiencies can be gained by incorporating auxiliary information derived from remote sensing (RS) into ground-based forest inventories. However, it can be difficult for countries embarking on NFI development to choose among the various RS integration options, and to develop a harmonized vision of how NFI and RS data can work together to meet monitoring needs. The NFI of the United States, which has been conducted by the USDA Forest Service’s (USFS) Forest Inventory and Analysis (FIA) program for nearly a century, uses RS technology extensively. Here we review the history of the use of RS in FIA, beginning with general background on NFI, FIA, and sampling statistics, followed by a description of the evolution of RS technology usage, beginning with paper aerial photography and ending with present day applications and future directions. The goal of this review is to offer FIA’s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs. Numéro de notice : A2020-844 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f11121364 Date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.3390/f11121364 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98632
in Forests > vol 11 n° 12 (December 2020) . - n° 1364[article]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)
[article]
Titre : 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 Type de document : Article/Communication Auteurs : Luka Jurjević, Auteur ; Xinlian Liang, Auteur ; Mateo Gašparović, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 227 - 241 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] balayage laser
[Termes IGN] corrélation
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] échantillonnage
[Termes IGN] forêt de feuillus
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de terrain
[Termes IGN] parcelle forestière
[Termes IGN] photogrammétrie métrologique
[Termes IGN] Quercus pedunculata
[Termes IGN] semis de pointsRésumé : (auteur) Tree height is one of the most important tree attributes in forest inventory. However, using conventional field methods to measure tree height is a laborious and time-consuming process. Despite the great interest in the past to facilitate tree height measurements, new, upcoming solutions are not yet thoroughly investigated. In this study, we investigated the applicability of different close-range remote sensing options for tree height measurement in a complex lowland deciduous forest. Six sample plots in a pedunculate oak forest were measured in detail using conventional methods. Close-range remote sensing datasets used in this study represent solutions from low-cost sensors used for hand-held personal laser scanning (PLShh), unmanned–borne laser scanning (ULS) and unmanned aerial vehicle photogrammetry (UAVimage). Each tree in the sample plots was interactively measured directly from the point cloud, and correspondence of the field- and remote sensing measured trees was verified using tree positions collected during fieldwork. Cross-comparisons of different datasets were performed to evaluate the performances of different data sources in the tree height estimation with respect to crown class, tree height and species. All remote sensing data sources correlated well, e.g. biases between remote sensing sources were around ± 1%. The field-measured tree height in general correlated well with remote sensing data sources. The uncertainties and bias of the field measurements were dependent on the tree height and crown class. Field measurements tended to underestimate codominant and intermediate trees at the approximately 1 m magnitude, whilst remote sensing data sources were robust to crown classes. Low-cost ULS used in this study, and very likely in general, may not have enough penetration capability when measuring low and mostly occluded trees, causing missed treetops. PLShh gave tree height estimates closer to the real tree height than those derived from conventional field measurements for trees above 21 m height. Numéro de notice : A2020-641 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.09.014 Date de publication en ligne : 03/10/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.09.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96064
in ISPRS Journal of photogrammetry and remote sensing > vol 169 (November 2020) . - pp 227 - 241[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020113 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020112 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt River ice segmentation with deep learning / Abhineet Singh in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)
[article]
Titre : River ice segmentation with deep learning Type de document : Article/Communication Auteurs : Abhineet Singh, Auteur ; Hayden Kalke, Auteur ; Mark Loewen, Auteur Année de publication : 2020 Article en page(s) : pp 7570 - 7579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage non-dirigé
[Termes IGN] apprentissage profond
[Termes IGN] Canada
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] glace
[Termes IGN] image captée par drone
[Termes IGN] rivière
[Termes IGN] segmentation d'image
[Termes IGN] segmentation sémantiqueRésumé : (auteur) This article deals with the problem of computing surface concentrations for two types of river ice from digital images acquired during freeze-up. It presents the results of attempting to solve this problem using several state-of-the-art semantic segmentation methods based on deep convolutional neural networks (CNNs). This task presents two main challenges—very limited availability of labeled training data and presence of noisy labels due to the great difficulty of visually distinguishing between the two types of ice, even for human experts. The results are used to analyze the extent to which some of the best deep learning methods currently in existence can handle these challenges. The code and data used in the experiments are made publicly available to facilitate further work in this domain. Numéro de notice : A2020-674 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2981082 Date de publication en ligne : 13/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2981082 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96165
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 11 (November 2020) . - pp 7570 - 7579[article]VNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada / Kathleen E. Johnson in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 11 (November 2020)
[article]
Titre : VNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada Type de document : Article/Communication Auteurs : Kathleen E. Johnson, Auteur ; Krzysztof Koperski, Auteur Année de publication : 2020 Article en page(s) : pp 695 - 700 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie géologique
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] image proche infrarouge
[Termes IGN] image Worldview
[Termes IGN] minéralogie
[Termes IGN] Nevada (Etats-Unis)
[Termes IGN] réalité de terrain
[Termes IGN] Short Waves InfraRedRésumé : (Auteur) Cuprite, Nevada, is a location well known for numerous studies of its hydrothermal mineralogy. This region has been used to validate geological interpretations of airborne hyperspectral imagery (AVIRIS HSI ), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ) imagery, and most recently eight-band WorldView-3 shortwave infrared (SWIR ) imagery. WorldView-3 is a high-spatial-resolution commercial multispectral satellite sensor with eight visible-to-near-infrared (VNIR ) bands (0.42–1.04 μm) and eight SWIR bands (1.2–2.33 μm). We have applied mineral mapping techniques to all 16 bands to perform a geological analysis of the Cuprite, Nevada, location. Ground truth for the training and validation was derived from AVIRIS hyperspectral data and United States Geological Survey mineral spectral data for this location. We present the results of a supervised mineral-mapping classification applying a random-forest classifier. Our results show that with good ground truth, WorldView-3 SWIR + VNIR imagery produces an accurate geological assessment. Numéro de notice : A2020-709 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.11.695 Date de publication en ligne : 01/11/2020 En ligne : https://doi.org/10.14358/PERS.86.11.695 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96395
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 11 (November 2020) . - pp 695 - 700[article]Réservation
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