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Auteur R. Henriques |
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UAV photogrammetry for topographic monitoring of coastal areas / J.A. Gonçalves in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)
[article]
Titre : UAV photogrammetry for topographic monitoring of coastal areas Type de document : Article/Communication Auteurs : J.A. Gonçalves, Auteur ; R. Henriques, Auteur Année de publication : 2015 Article en page(s) : pp 101 - 111 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Agisoft Photoscan
[Termes IGN] chambre non métrique
[Termes IGN] drone
[Termes IGN] dune
[Termes IGN] modèle numérique de surface
[Termes IGN] photogrammétrie numérique
[Termes IGN] plage
[Termes IGN] point d'appui
[Termes IGN] Portugal
[Termes IGN] semis de points
[Termes IGN] surveillance du littoralRésumé : (auteur) Coastal areas suffer degradation due to the action of the sea and other natural and human-induced causes. Topographical changes in beaches and sand dunes need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution of these natural environments. This is an important application for airborne LIDAR, and conventional photogrammetry is also being used for regular monitoring programs of sensitive coastal areas. This paper analyses the use of unmanned aerial vehicles (UAV) to map and monitor sand dunes and beaches. A very light plane (SwingletCam) equipped with a very cheap, non-metric camera was used to acquire images with ground resolutions better than 5 cm. The Agisoft Photoscan software was used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. The processing, which includes automatic aerial triangulation with camera calibration and subsequent model generation, was mostly automated. To achieve the best positional accuracy for the whole process, signalised ground control points were surveyed with a differential GPS receiver. Two very sensitive test areas on the Portuguese northwest coast were analysed. Detailed DSMs were obtained with 10 cm grid spacing and vertical accuracy (RMS) ranging from 3.5 to 5.0 cm, which is very similar to the image ground resolution (3.2–4.5 cm). Where possible to assess, the planimetric accuracy of the orthoimage mosaics was found to be subpixel. Within the regular coastal monitoring programme being carried out in the region, UAVs can replace many of the conventional flights, with considerable gains in the cost of the data acquisition and without any loss in the quality of topographic and aerial imagery data. Numéro de notice : A2015--002 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78337
in ISPRS Journal of photogrammetry and remote sensing > vol 104 (June 2015) . - pp 101 - 111[article]Carto-Som: Cartogram creation using self-organizing maps / R. Henriques in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)
[article]
Titre : Carto-Som: Cartogram creation using self-organizing maps Type de document : Article/Communication Auteurs : R. Henriques, Auteur ; Fernando Bacao, Auteur ; V. Lobo, Auteur Année de publication : 2009 Article en page(s) : pp 483 - 511 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] carte de Kohonen
[Termes IGN] cartogramme
[Termes IGN] classification par réseau neuronal
[Termes IGN] représentation cartographiqueRésumé : (Auteur) The basic idea of a cartogram is to distort a geographical map by substituting the geographic area of a region by some other variable of interest. The objective is to rescale each region according to the value of the variable of interest while keeping the map, as much as possible, recognizable. There are several algorithms for building cartograms. None of these methods has proved to be universally better than any other, since the trade-offs made to get the correct distortion vary. In this paper we present a new method for building cartograms, based on self-organizing neural networks (Kohonen's self-organizing maps or SOM). The proposed method is widely available and is easy to carry out, and yet has several appealing properties, such as easy parallelization, making up a good tool for geographic data presentation and analysis. We present a series of tests on different problems, comparing the new algorithm with existing ones. We conclude that it is competitive and, in some circumstances, can perform better then existing algorithms. Copyright Taylor & Francis Numéro de notice : A2009-160 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810801958885 En ligne : https://doi.org/10.1080/13658810801958885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29790
in International journal of geographical information science IJGIS > vol 23 n°3-4 (march - april 2009) . - pp 483 - 511[article]Réservation
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