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Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices / A.S. Rogers in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 25 n° 12 (June 2004) . - pp 2317 - 2335 Titre : Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices Type de document : Article/Communication Auteurs : A.S. Rogers, Auteur ; M.S. Kearney, Auteur Année de publication : 2004 Article en page(s) : pp 2317 - 2335 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] grande échelle [Termes IGN] image Landsat-TM [Termes IGN] interprétation automatique [Termes IGN] littoral [Termes IGN] marais [Termes IGN] méthode robuste [Termes IGN] réflectance [Termes IGN] sédiment [Termes IGN] signature spectrale [Termes IGN] zone humide Résumé : (Auteur) Evidence of the rapid losses of coastal marshes calls for the application of remote sensing data. Nonetheless, many features indicative of incipient marsh loss, such as widening of tidal creeks and formation of small ponds, are often not readily detectable at the nominal 30 a x 30 m resolution of Thematic Mapper (TM) imagery, the general source for conventional satellite sensor-based data on wetlands. Spectral mixture modelling, where the proportional representation of land cover types can be estimated within pixels, offers a potential solution to the problem of assessing initial indications of loss in coastal marshes. Nevertheless, the simple linear mixture models most commonly employed can be subject to significant errors when applied to marshes due to the considerable variety of soil/sediment types in these environments. A new method is presented here which not only successfully reduces the spectral variability of soils, but also in the other principal components of vegetation and water, to a three-endmember model for estimating their fractional representation in TM data. Fractional representations for these variables in this method yield more reliable results than those obtained from unmixing corrected reflectance data. Though unmixing individual scenes may still be best achieved by extensive ground-referencing and image analysis, this technique is a robust approach for large-scale, semi-automated processing of many scenes in investigations of marsh surface condition. Numéro de notice : A2004-222 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001618103 En ligne : https://doi.org/10.1080/01431160310001618103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26749 [article]

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