Mapping coloured dissolved organic matter concentration in coastal waters

International Journal of Remote Sensing

Volumn 30, Issue 22, 2009, Pages 5843-5849

  Kutser, T ^a   Paavel, B ^a   Metsamaa, L ^a   Vahtma E ^a  

^a UNIVERSITY OF TARTU   (Estonia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOGEOCHEMISTRY; BIOLOGICAL MATERIALS; MAPPING; OPTICAL PROPERTIES; ORGANIC COMPOUNDS;

ADVANCED LAND IMAGERS; COASTAL ENVIRONMENTS; COLOURED DISSOLVED ORGANIC MATTERS; CONCENTRATION RANGES; HIGH SPATIAL RESOLUTION; RADIOMETRIC RESOLUTION; REMOTE SENSING INSTRUMENTS; RETRIEVAL ALGORITHMS;

REMOTE SENSING;

ALGORITHM; COASTAL WATER; CONCENTRATION (COMPOSITION); DISSOLVED ORGANIC MATTER; MAPPING; OPTICAL PROPERTY; REMOTE SENSING; SPATIAL RESOLUTION;

ATLANTIC OCEAN; BALTIC SEA;

EID: 70449378785     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160902744837     Document Type: Article

References (15)

1. ARST, H., ERM, A., HERLEVI, A., KUTSER, T., LEPPÄRANTA, M., REINART, A. and VIRTA, J., 2008, Optical properties of boreal lake waters in Finland and Estonia. Boreal Environment Research, 13, pp. 133-158.
2. CHEN, C., SHI, P. and ZHAN H., 2003, A local algorithm for estimation of yellow substance (gelbstoff) in coastal waters from SeaWiFS data: Pearl River estuary, China. International Journal of Remote Sensing, 24, pp. 1171-1176.
3. CLEMENTSON, L.A., PARSLOW, J.S., TURNBULL, A.R. and BONHAM, P.I., 2004, Properties of light absorption in highly coloured estuarine system in south-east Australia which is prone to blooms of the toxic dinoflagellate Gymnodinium catenatum. Estuarine, Coastal and Shelf Science, 60, pp. 101-112.
4. DARECKI, M. and STRAMSKI, D., 2004, An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea. Remote Sensing of Environment, 89, pp. 326-350.
5. DOXARAN, D., CHERUKURU, R.C.N. and LAVENDER S.J., 2005, Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters. International Journal of Remote Sensing, 26, pp. 1763-1769.
6. KALLIO, K., KUTSER, T., HANNONEN, T., KOPONEN, S., PULLIAINEN, J., VEPSÄLÄINEN, J. and PYHÄLAHTI, T., 2001, Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons. The Science of the Total Environment, 268, pp. 59-77.
7. KOWALCZUK, P., OLSZEWSKI, J.,DARECKI,M. and KACZMAREK, S., 2005, Empirical relationships between coloured dissolved organic matter(CDOM) absorption and apparent optical properties in Baltic Sea waters. International Journal of Remote Sensing, 26, pp. 345-370.
8. KUTSER, T., 2004, Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing. Limnology and Oceanography, 49, pp. 2179-2189.
9. KUTSER, T., ARST, H., MÄEKIVI, S. and KALLASTE, K., 1998, Estimation of the water quality of the Baltic Sea and some lakes in Estonia and Finland by passive optical remote sensing measurements on board a vessel. Lakes and Reservoirs; Research and Management, 3, pp. 53-66.
10. KUTSER, T., HERLEVI, A., KALLIO,K. and ARST, H., 2001, A hyperspectral model for interpretation of passive optical remote sensing data from turbid lakes, The Science of the Total Environment, 268, pp. 47-58.
11. KUTSER, T., PIERSON, D.C., TRANVIK, L., REINART, A., SOBEK, S. and KALLIO, K., 2005a, Estimating the colored dissolved organic matter absorption coefficient in lakes using satellite remote sensing. Ecosystems, 8, pp. 709-720.
12. KUTSER, T., PIERSON, D. C., KALLIO, K., REINART, A. and SOBE K, S., 2005b, Mapping lake CDOM by satellite remote sensing. Remote Sensing of Environment, 94, pp. 535-540.
13. REINART, A. and KUTSER, T., 2006, Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea. Remote Sensing of Environment, 102, pp. 74-85
14. SCHWARZ, J.N., 2005, Derivation of dissolved organic carbon concentrations from Sea WiFS data. International Journal of Remote Sensing, 26, pp. 283-293.
15. VAHTMÄE, E., KUTSER, T.,MARTIN, G. and KOTTA, J., 2006, Feasibility of hyperspectral remote sensing for mapping benthic macroalgal cover in turbid coastal waters. Remote Sensing of Environment, 101, pp. 342-351.