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EARSeL 2013, 8th Imaging Spectrometry Workshop 08/04/2013 10/04/2013 Nantes France
nom du congrès :
EARSeL 2013, 8th Imaging Spectrometry Workshop
début du congrès :
08/04/2013
fin du congrès :
10/04/2013
ville du congrès :
Nantes
pays du congrès :
France
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Very high resolution urban land cover extraction using airborne hyperspectral images / Arnaud Le Bris (April 2013)
Titre : Very high resolution urban land cover extraction using airborne hyperspectral images Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Editeur : Paris : European Association of Remote Sensing Laboratories EARSEL Année de publication : April 2013 Conférence : EARSeL 2013, 8th Imaging Spectrometry Workshop 08/04/2013 10/04/2013 Nantes France Importance : 8 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] caméra numérique
[Termes IGN] capteur aérien
[Termes IGN] classification
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] villeRésumé : (auteur) During last decade, needs for high resolution land cover data have been growing. Such knowledge is namely often required in environment monitoring studies. Thus, to answer these needs, national mapping or environment agencies, in many countries, have undertaken the production of such large scale national land cover database. Nevertheless, these databases provide a general classification and may not suit some specific (often new) applications requiring a semantic or geometric finer level of details. That is to say that, on one hand, additional land cover classes should sometimes be specified, whereas, on the other hand, some existing classes should be delineated at a finer level.
More particularly, in urban areas, knowledge concerning very high resolution land cover and especially material classification are necessary for several city modelling applications. Most of these applications are still experimental scientific ones in various fields such as micro-meteorology, hydrology, pollutants flow monitoring and ground perviousness monitoring. Thus, knowledge concerning the roofing materials or the different kinds of ground areas (pervious, vegetated, impervious…) are required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale since no existing map contains such information. However, remote sensing imagery of urban environments from airborne acquisitions namely still remains a major scientific issue, since on one hand, urban areas are characterized by a high variety of materials, and on the other hand, results provided by most of the traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral imagery.
Thus, the present experiments are part of a work aiming at designing a future superspectral camera system dedicated to high resolution urban land cover classification applications, and especially material mapping. The choice of optimal band sets will here be processed from a set of airborne hyperspectral data.
A data acquisition campaign named UMBRA has recently been carried out thanks to the French collaboration of IGN and ONERA. Data have been captured over two French cities chosen for their difference in building architecture, urbanization planning and their variety in urban material. Airborne images have been acquired simultaneously by multispectral and hyperspectral cameras with a ground sampling distance ranging from 0.12m for multispectral to 1.6m for hyperspectral in the SWIR channels. The images were radiometrically and geometrically calibrated and have a noticeable low signal-to-noise ratio.
The first urban land cover / material classification results obtained from this new reference data set will be presented in this paper.Numéro de notice : C2013-043 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80250 Documents numériques
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