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Titre : UAV photogrammetry and remote sensing Type de document : Monographie Auteurs : Fernando Carvajal-Ramírez, Éditeur scientifique ; Francisco Agüera-Vega, Éditeur scientifique ; Patricio Martínez-Carricondo, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 258 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-0365-1453-6 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image captée par drone
[Termes IGN] indice de végétation
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] occupation du sol
[Termes IGN] orthophotographie
[Termes IGN] photogrammétrie aérienne
[Termes IGN] point d'appui
[Termes IGN] reconstruction 3D
[Termes IGN] réseau antagoniste génératif
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] zone tamponRésumé : (éditeur) The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites.The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained.More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products.This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry. Note de contenu : 1- Using UAV-based photogrammetry to obtain correlation between the vegetation indices and chemical analysis of agricultural crops
2- Photogrammetry using UAV-mounted GNSS RTK: Georeferencing strategies without GCPs
3- Quality assessment of photogrammetric methods—A workflow for reproducible UAS orthomosaics
4- 3D reconstruction of power lines using UAV images to monitor corridor clearance
5- UAV-based terrain modeling under vegetation in the Chinese Loess Plateau: A deep learning and terrain correction ensemble frameword
6- UAV photogrammetry accuracy assessment for corridor mapping based on the number and distribution of ground control points
7- UAV + BIM: Incorporation of photogrammetric techniques in architectural projects with building information modeling versus classical work processes
8- Structure from motion of multi-angle RPAS imagery complements larger-scale airborne Lidar data for cost-effective snow monitoring in mountain forests
9- Use of UAV-photogrammetry for quasi-vertical wall surveying
10- Deep learning-based single image super-resolution: An investigation for dense scene reconstruction with UAS photogrammetry
11- Mapping heterogeneous urban landscapes from the fusion of digital surface model and unmanned aerial vehicle-based images using adaptive multiscale image segmentation and classificationNuméro de notice : 28664 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1453-6 En ligne : https://doi.org/10.3390/books978-3-0365-1453-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99850