Centre de documentation
scientifique

Extending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring / J.D. Shutler in Remote sensing of environment, vol 107 n° 4 (30/04/2007)  

Public [article]  inRemote sensing of environment > vol 107 n° 4 (30/04/2007) . - pp 521 - 532 Titre : Extending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring Type de document : Article/Communication Auteurs : J.D. Shutler, Auteur ; P.E. Land, Auteur ; S.B. Groom, Auteur Année de publication : 2007 Article en page(s) : pp 521 - 532 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] chlorophylle [Termes IGN] correction atmosphérique [Termes IGN] couleur de l'océan [Termes IGN] données de terrain [Termes IGN] données spatiotemporelles [Termes IGN] image Aqua-MODIS [Termes IGN] image Terra-MODIS [Termes IGN] littoral [Termes IGN] qualité des eaux [Termes IGN] surveillance écologique Résumé : (Auteur) National and regional obligations to control and maintain water quality have led to an increase in coastal and estuarine monitoring. A potentially valuable tool is high temporal and spatial resolution satellite ocean colour data. NASA's MODIS-Terra and -Aqua can capture data at both 250 m and 500 m spatial resolutions and the existence of two sensors provides the possibility for multiple daily passes over a scene. However, no robust atmospheric correction method currently exists for these data, rendering them unusable for quantitative monitoring applications. Therefore, this paper presents an automatic and dynamic atmospheric correction approach allowing the determination of ocean colour. The algorithm is based around the standard MODIS 1 km atmospheric correction, includes cloud masking and is applicable to all of the visible 500 m bands. Comparison of the 500 m ocean colour data with the standard 1 km data shows good agreement and these results are further supported by in situ data comparisons. In addition, a novel method to produce 500 m chlorophyll-a estimates is presented. Comparisons of the 500 m estimates with the standard MODIS OC3M algorithm and to in situ data from a near-coast validation site are given. Copyright Elsevier Numéro de notice : A2007-157 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.10.004 En ligne : https://doi.org/10.1016/j.rse.2006.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28520 [article]

SeaWIFS discrimination of harmful algal bloom evolution / P.I. Miller in International Journal of Remote Sensing IJRS, vol 27 n° 11 (June 2006)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 27 n° 11 (June 2006) . - pp 2287 - 2301 Titre : SeaWIFS discrimination of harmful algal bloom evolution Type de document : Article/Communication Auteurs : P.I. Miller, Auteur ; J.D. Shutler, Auteur ; G.F. Moore, Auteur ; S.B. Groom, Auteur Année de publication : 2006 Article en page(s) : pp 2287 - 2301 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] algue [Termes IGN] analyse diachronique [Termes IGN] analyse multivariée [Termes IGN] Baltique, mer [Termes IGN] couleur de l'océan [Termes IGN] image Seawifs [Termes IGN] Manche (mer) [Termes IGN] Nord, mer du [Termes IGN] série temporelle [Termes IGN] température de surface de la mer Résumé : (Auteur) The discrimination of harmful algal blooms (HABs) from space would benefit both the capability of early warning systems and the study of environmental factors affecting the initiation of blooms. Unfortunately, there are no published techniques using global monitoring satellite sensors to distinguish the resulting subtle changes in ocean colour, so in situ sampling is needed to identify the species in any observed bloom. This paper investigates multivariate classification as an objective means to discriminate harmful and harmless algae and monitor their dynamics using ocean colour data derived from satellite sensors. The classifier is trained and tested using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data, though the method is designed to be generic for other sensors. Time-series results are presented using the new HAB likelihood index and suggest that SeaWiFS has some capability for observing the dynamic evolution of harmful blooms of Karenia mikimotoi, Chattonella verruculosa and cyanobacteria. Further, a multi-band spatial subtraction algorithm is described to automate the identification of bloom regions and improve the accuracy in discriminating HABs. Copyright Taylor & Francis Numéro de notice : A2006-301 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500396816 En ligne : https://doi.org/10.1080/01431160500396816 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28028 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-06061	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt