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The coregistration, calibration, and interpretation of multiseason JERS-1 SAR data over South America / Paul Siqueira in Remote sensing of environment, vol 87 n° 4 (15/11/2003)
[article]
Titre : The coregistration, calibration, and interpretation of multiseason JERS-1 SAR data over South America Type de document : Article/Communication Auteurs : Paul Siqueira, Auteur ; B. Chapman, Auteur ; G. Mcgarragh, Auteur Année de publication : 2003 Article en page(s) : pp 389 - 403 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Amazonie
[Termes IGN] analyse diachronique
[Termes IGN] bande L
[Termes IGN] biosphère
[Termes IGN] écosystème
[Termes IGN] étalonnage radiométrique
[Termes IGN] image JERS
[Termes IGN] précision infrapixellaireRésumé : (Auteur) The Large-Scale Biosphere-Atmosphere (LBA) experiment in Amazonia represents a unique opportunity to make a comprehensive study of the Amazon region and its components ecosystems. To make sense of the field studies and to generalize the results from them, remote sensing techniques and comprehensive mapping are critical elements for producing region-wide science results. In this paper, we present the processing work done for one such mapping campaign, that of the JERS-1 L-band two season (low and high flood) SAR data collected in 1995 and 1996. Specifically, to make a useable resource for other LBA researchers to explore, the datasets from the two seasons had to be coregistred (to a sub-pixel level), radiometrically calibrated, and interpreted to verify the quality of the data. This paper describes the techniques used to achieve these goals and estimate of the land cover based on a simple classification of the data. Numéro de notice : A2003-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2002.12.002 Date de publication en ligne : 21/10/2003 En ligne : https://doi.org/10.1016/j.rse.2002.12.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22632
in Remote sensing of environment > vol 87 n° 4 (15/11/2003) . - pp 389 - 403[article]Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network / A.J. Tatem in International journal of geographical information science IJGIS, vol 17 n° 7 (october 2003)
[article]
Titre : Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network Type de document : Article/Communication Auteurs : A.J. Tatem, Auteur ; H.G. Lewis, Auteur ; P.M. Atkinson, Auteur ; M.S. Nixon, Auteur Année de publication : 2003 Article en page(s) : pp 647 - 672 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte agricole
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par réseau neuronal
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Grèce
[Termes IGN] image Landsat-TM
[Termes IGN] image satellite
[Termes IGN] incertitude géométrique
[Termes IGN] limite de résolution géométrique
[Termes IGN] occupation du sol
[Termes IGN] précision infrapixellaireRésumé : (Auteur) Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a 'best guess' prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the subpixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of smallscale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of pratical remotly sensed imagery at the sub pixel scale. Numéro de notice : A2003-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/1365881031000135519 En ligne : https://doi.org/10.1080/1365881031000135519 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22553
in International journal of geographical information science IJGIS > vol 17 n° 7 (october 2003) . - pp 647 - 672[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-03071 RAB Revue Centre de documentation En réserve L003 Disponible 079-03072 RAB Revue Centre de documentation En réserve L003 Disponible Photogrammetric target location to subpixel accuracy in digital images / E.M. Mikhail (1983)
Titre : Photogrammetric target location to subpixel accuracy in digital images : 39th Photogrammetric Week Type de document : Actes de congrès Auteurs : E.M. Mikhail, Auteur Congrès : PW 1983, 39th Photogrammetric Week (19 - 24 septembre 1983; Stuttgart, Allemagne), Auteur Editeur : West Lafayette (Indiana) : Purdue University Année de publication : 1983 Importance : 25 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] image numérique
[Termes IGN] méthode des moindres carrés
[Termes IGN] précision infrapixellaire
[Termes IGN] reconnaissance de formesIndex. décimale : CG1983 Actes de congrès en 1983 Numéro de notice : 57052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Actes Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=35878 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 57052-01 CG.83 Livre Centre de documentation En réserve M-103 Disponible