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dc.contributor.authorDahanayaka, D.D.G.L.-
dc.contributor.authorTonooka, H.-
dc.contributor.authorWijeyaratne, M.J.S.-
dc.contributor.authorMinato, A.-
dc.contributor.authorOzawa, S.-
dc.date.accessioned2014-12-12T09:13:09Z-
dc.date.available2014-12-12T09:13:09Z-
dc.date.issued2015-
dc.identifierZoologyen_US
dc.identifier.citationDahanayakage Don Gihan Lakmal Dahanayaka, Hideyuki Tonooka, Jayantha Wijeyaratne, Atsushi Minato & Satoru Ozawa (2015) Malaysian Journal of Remote Sensing & GIS (MJRS&GIS), Vol. 4, Number 1, 21-29en_US
dc.identifier.urihttp://www.igrsm.com/mjrsgis/issues.html-
dc.description.abstractIn the present study, we compare the following Chlorophyll–a (Chl-a) estimation algorithms using ASTER data acquired over Sri Lankan coastal water bodies: (1) the simple band-ratio algorithm with simple atmospheric correction using dark object subtraction (DOS); (2) the single band-ratio algorithm with radiative transfer-based atmospheric correction using ENVI’s FLAASH software including MODTRAN; and (3) our previously proposed algorithm based on combinations of ASTER and corrected MODIS Ocean Color-3 (OC3) data. First, several ASTER band ratios were regressively analyzed with in-situ Chl-a data acquired from the Negombo estuary and Puttalam lagoon in the west coast of Sri Lanka, and the band ratio with the highest correlation was selected. Then, time-series Chl-a distribution maps with the spatial resolution of ASTER/VNIR (15 m) were generated using the above three methods, and compared with the in-situ Chl-a data. Based on the result obtained, the FLAASH and ASTER/OC3 based methods showed high correlation with the in-situ Chl-a values (R2 = 0.96 and 0.92 respectively), while the DOS based method showed low correlation (R2 = 0.61), which indicates that the ASTER/OC3 based method will give equivalent performance to the FLAASH based method even though it does not need user-based atmospheric correction like the DOS and the FLAASH based methods.en_US
dc.language.isoEnglishen_US
dc.publisherMalaysian Journal of Remote Sensing & GIS (MJRS&GIS)en_US
dc.titleComparison of three chlorophyll-a estimation approaches using ASTER data acquired over Sri Lankan coastal water bodiesen_US
dc.typeArticleen_US
Appears in Collections:Zoology

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