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An in-depth simulation of EnMAP acquisition geometry / P. Schwind in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 99 - 106 Titre : An in-depth simulation of EnMAP acquisition geometry Type de document : Article/Communication Auteurs : P. Schwind, Auteur ; R. Muller, Auteur ; G. Palubinskas, Auteur ; T. Storch, Auteur Année de publication : 2012 Article en page(s) : pp 99 - 106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] capteur spatial [Termes IGN] image EnMAP [Termes IGN] qualité géométrique (image) [Termes IGN] rayonnement infrarouge lointain [Termes IGN] rayonnement proche infrarouge [Termes IGN] simulation d'image Résumé : (Auteur) The future hyperspectral satellite EnMAP (Environmental Mapping and Analysis Program) uses two separate sensors for the acquisition of VNIR and SWIR imagery. Due to their geometric configuration, the SWIR and VNIR instruments map the same positions on the ground with a time delay of 88 ms. Coupled with attitude controller inaccuracies this leads to an estimated co-registration error between SWIR and VNIR higher than the maximum 0.2 pixels designated in the specifications of EnMAP imagery. It is assumed that, by approximating or interpolating the real attitude and geometrically correcting the images, this co-registration error can be significantly reduced. To validate these assumptions, a geometric simulator was developed at the German Aerospace Center DLR which is responsible for the development of the ground segment of EnMAP. The implemented simulator, together with an evaluation of the absolute and relative accuracy, performed using this simulator, are presented in this article. The obtained results demonstrate that the desired co-registration accuracy between SWIR and VNIR imagery can be achieved by using Spline or Chebyshev approximation for the attitude reconstruction but not by using Lagrange interpolation. Numéro de notice : A2012-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31737 [article]

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081-2012041	SL	Revue	Centre de documentation	Revues en salle	Disponible

Orthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data / Peter Reinartz in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 66 n° 1 (January - February 2011) . - pp 124 - 132 Titre : Orthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data Type de document : Article/Communication Auteurs : Peter Reinartz, Auteur ; R. Muller, Auteur ; P. Schwind, Auteur ; et al., Auteur Année de publication : 2011 Article en page(s) : pp 124 - 132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'images [Termes IGN] erreur moyenne quadratique [Termes IGN] image ALOS-PRISM [Termes IGN] image Ikonos [Termes IGN] image optique [Termes IGN] image radar [Termes IGN] image TerraSAR-X [Termes IGN] méthode robuste [Termes IGN] modèle par fonctions rationnelles [Termes IGN] orientation du capteur [Termes IGN] orthorectification [Termes IGN] point d'appui [Termes IGN] précision géométrique (imagerie) [Termes IGN] zone urbaine Résumé : (Auteur) Orthorectification of satellite data is one of the most important pre-processing steps for application oriented evaluations and for image data input into Geographic Information Systems. Although high- and very high-resolution optical data can be rectified without ground control points (GCPs) using an underlying digital elevation model (DEM) to positional root mean square errors (RMSEs) between 3 m and several hundred meters (depending on the satellite), there is still need for ground control with higher precision to reach lower RMSE values for the orthoimages. The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations. This is due to the fact that the SAR antenna measures distances which are mainly dependent on the terrain height and the position of the satellite. The latter can be measured with high precision, whereas the satellite attitude need not be known exactly. If the used DEM is of high accuracy, the resulting geocoded SAR data are very precise in their geolocation. This precision can be exploited to improve the orientation knowledge and thereby the geometric accuracy of the rectified optical satellite data. The challenge is to match two kinds of image data, which exhibit very different geometric and radiometric properties. Simple correlation techniques do not work and the goal is to develop a robust method which works even for urban areas, including radar shadows, layover and foreshortening effects. First the optical data have to be rectified with the available interior and exterior orientation data or using rational polynomial coefficients (RPCs). From this approximation, the technique used is the measurement of small identical areas in the optical and radar images by automatic image matching, using a newly developed adapted mutual information procedure followed by an estimation of correction terms for the exterior orientation or the RPC coefficients. The matching areas are selected randomly from a regular grid covering the whole imagery. By adjustment calculations, parameters from falsely matched areas can be eliminated and optimal improvement parameters are found. The original optical data are orthorectified again using the delivered metadata together with these corrections and the available DEM. As proof of method the orthorectified data from IKONOS and ALOS-PRISM sensors are compared with conventional ground control information from high-precision orthoimage maps of the German Cartographic Survey. The results show that this method is robust, even for urban areas. Although the resulting RMSE values are in the order of 2–6 m, the advantage is that this result can be reached even for optical sensors which do not exhibit low RMSE values without using manual GCP measurements. Numéro de notice : A2011-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.10.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.10.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30799 [article]

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