Photogrammetric Engineering & Remote Sensing, PERS / American society for photogrammetry and remote sensing . vol 71 n° 8Paru le : 01/08/2005 ISBN/ISSN/EAN : 0099-1112 |
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Ajouter le résultat dans votre panierBias-compensated RPCs [rational polynomial coefficient] for sensor orientation of high-resolution satellite imagery / Clive Simpson Fraser in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 8 (August 2005)
[article]
Titre : Bias-compensated RPCs [rational polynomial coefficient] for sensor orientation of high-resolution satellite imagery Type de document : Article/Communication Auteurs : Clive Simpson Fraser, Auteur ; B. Hanley, Auteur Année de publication : 2005 Article en page(s) : pp 909 - 915 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] chambre métrique
[Termes IGN] compensation par faisceaux
[Termes IGN] distorsion d'image
[Termes IGN] erreur systématique
[Termes IGN] géoréférencement
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] image Quickbird
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] orientation du capteurRésumé : (Auteur) The demand for higher quality metric products from high-resolution satellite imagery (HRSI) is growing, and the number HRSI sensors and product options is increasing. There is a greater need to fully understand the potential and indeed shortcomings of alternative photogrammetric sensor orientation models for HRSI. To date, rational functions have proven to be a viable alternative model for geo-positioning, and with the recent innovation of bias-compensated RPC bundle-adjustment, it has been demonstrated that sensor orientation to subpixel level can be achieved with minimal ground-control. Questions have lingered, however, as to the general suitability of bias-compensated rational polynomial coefficients (RPCs), and indeed rational functions in general. The purpose of this paper is to demonstrate the wide applicability of bias-compensated RPCs for high accuracy geopositioning from stereo HRSI. The case of stereo imagery over mountainous, terrain will be specifically addressed, and results of experimental testing of both Ikonos and QuickBird imagery will be presented. Numéro de notice : A2005-336 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.8.909 En ligne : https://doi.org/10.14358/PERS.71.8.909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27472
in Photogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 8 (August 2005) . - pp 909 - 915[article]Comparing raster map for spatial modelling and analysis / M. Kuhnert in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 8 (August 2005)
[article]
Titre : Comparing raster map for spatial modelling and analysis Type de document : Article/Communication Auteurs : M. Kuhnert, Auteur ; A. Voinov, Auteur ; R. Seppelt, Auteur Année de publication : 2005 Article en page(s) : pp 975 - 984 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] algorithme de tri
[Termes IGN] analyse comparative
[Termes IGN] analyse spatiale
[Termes IGN] cartographie numérique
[Termes IGN] données mailléesRésumé : (Auteur) The comparison of spatial patterns is recognized as an important task in landscape ecology especially when spatially explicit simulation modeling or remote sensing is applied. Yet, there is no agreed procedure for doing that, probably because different problems require different algorithms. We explored a variety of existing algorithms and modified some of them to compare grid-based maps with categorical attributes. A new algorithm based on the "expanding window" approach was developed and compared to other known algorithms. The goal was to offer simple and flexible procedures for comparing spatial patterns in grid based maps that do not take into consideration object shapes and sizes of the maps. The difference between maps was characterized by three values: quantity, location, and distance between corresponding categories in the maps. Combinations of these indices work as good criteria to quantify differences between maps. A web-based survey was set up, in which participants were asked to grade the similarity of ten pairs of maps. These results were then used to compare how well the various algorithms can perform relative to the visual comparisons obtained; they were also used to calibrate existing algorithms. Numéro de notice : A2005-337 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14358/PERS.71.8.975 En ligne : https://doi.org/10.14358/PERS.71.8.975 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27473
in Photogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 8 (August 2005) . - pp 975 - 984[article]