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Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data / Y. Oyama in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)
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Titre : Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data Type de document : Article/Communication Auteurs : Y. Oyama, Auteur ; B. Matsushita, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 73 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] analyse discriminante
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] décomposition d'image
[Termes IGN] image Landsat-TM
[Termes IGN] Japon
[Termes IGN] lac
[Termes IGN] matière organique
[Termes IGN] modélisation radiométrique de prise de vue
[Termes IGN] qualité des eaux
[Termes IGN] sédiment
[Termes IGN] turbidité des eauxRésumé : (Auteur) The remote sensing of Case 2 water has been far less successful than that of Case 1 water, due mainly to the complex interactions among optically active substances (e.g., phytoplankton, suspended sediments, colored dissolved organic matter, and water) in the former. To address this problem, we developed a spectral decomposition algorithm (SDA), based on a spectral linear mixture modeling approach. Through a tank experiment, we found that the SDA-based models were superior to conventional empirical models (e.g. using single band, band ratio, or arithmetic calculation of band) for accurate estimates of water quality parameters. In this paper, we develop a method for applying the SDA to Landsat-5 TM data on Lake Kasumigaura, a eutrophic lake in Japan characterized by high concentrations of suspended sediment, for mapping chlorophyll-a (Chl-a) and non-phytoplankton suspended sediment (NPSS) distributions. The results show that the SDA-based estimation model can be obtained by a tank experiment. Moreover, by combining this estimation model with satellite-SRSs (standard reflectance spectra : i.e., spectral endmembers) derived from biooptical modeling, we can directly apply the model to a satellite image. The same SDA-based estimation model for Chl-a concentration was applied to two Landsat-5 TM images, one acquired in April 1994 and the other in February 2006. The average Chl-a estimation error between the two was 9.9%, a result that indicates the potential robustness of the SDA-based estimation model. The average estimation error of NPSS concentration from the 2006 Landsat-5 TM image was 15.9%. The key point for successfully applying the SDA-based estimation model to satellite data is the method used to obtain a suitable satellite-SRS for each end-member. Numéro de notice : A2009-029 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.04.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29659
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 1 (January - February 2009) . - pp 73 - 85[article]Réservation
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