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Możliwości teledetekcyjnego monitorowania zawartości chlorofilu-a w wodach śródlądowych

Treść / Zawartość
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Warianty tytułu
EN
Possibilities of the monitoring of chlorophyll-a concentration in inland water using remote sensing techniques
Języki publikacji
PL
Abstrakty
EN
The variety of satellite data accessible at present gives the wide possibilities for the surface waters quality monitoring in case of size of monitored area (the size of satellite scene), possibility of obtaining the different water quality parameters (different spectral bands) and the precision of spatial distribution those parameters (pixel size). The chlorophyll-a, basic hydrobiological parameter, is the main index of the phytoplankton content in water. Remote sensing monitoring of chlorophyll-a concentration in case of sea and oceanic waters has been made for many years. Many computational formulae in reference to inland waters was elaborated for individual lakes or the types of lakes, but there is no universal formula independent from kind of water basin. The article presents the part of results of study made from 2003 for two tested areas, the Mazurian lakes and the Vistula Lagoon. The elaboration of the processing methodology of the superspectral CHRIS satellite data for the inland waters quality assessment was the main aim of this study. at present gives the wide possibilities for the surface waters quality monitoring in case of size of monitored area (the size of satellite scene), possibility of obtaining the different water quality parameters (different spectral bands) and the precision of spatial distribution those parameters (pixel size). The chlorophyll-a, basic hydrobiological parameter, is the main index of the phytoplankton content in water. Remote sensing monitoring of chlorophyll-a concentration in case of sea and oceanic waters has been made for many years. Many computational formulae in reference to inland waters was elaborated for individual lakes or the types of lakes, but there is no universal formula independent from kind of water basin. The article presents the part of results of study made from 2003 for two tested areas, the Mazurian lakes and the Vistula Lagoon. The elaboration of the processing methodology of the superspectral CHRIS satellite data for the inland waters quality assessment was the main aim of this study.
Rocznik
Tom
Strony
59--68
Opis fizyczny
Bibliogr. 23 poz., rys., wykr.
Twórcy
  • Wydział Geodezji i Kartografii, Wydział Inżynierii Politechniki Warszawskiej
Bibliografia
  • 1. Dekker A. G., 1993. Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing. PhD Thesis, Proeschrift Vrije Universiteit, Amsterdam, The Netherlands, s.1-240.
  • 2. Dekker A. G., Peters S.W.M., 1993. The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands. International Journal of Remote Sensing, vol. 14 (5), s. 799-821.
  • 3. Flink P., Lindell T., Ostlund C., 2001. Statistical analysis of hyperspectral data from two Swedish lakes. The Science of the Total Environment, vol. 268, s. 155-169.
  • 4. Ghezzi P., Giardino C., Pepe M., Zilioli E., 1998. Report on the 2nd Salmon joint meeting, Venice, s. 10-11.
  • 5. Giardino C., Brivio P. A., Zilioli E., 1997. Comparison of satellite and airborne Thematic Mapper data for estimating inland water quality. W: Earth surface Remote Sensing. Cecchi G., Engman E. T., Zilioli E. Editors, SPIE, 3222, s. 211-217.
  • 6. Gitelson A., Szilagyi F., Garbuzov G., Mittenzwey K.-H., 1994. Remote Sensing estimation of inland and coastal waters quality.
  • 7. Harding L. W., Itsweire E. C., Esaias W. E., 1995. Algorithm development chlorophyll concentrations in Chesapeake Bay using aircraft remote sensing. Photogrammetric Engineering and Remote Sensing, vol. 61, s. 177-185.
  • 8. Harma P., Vepsalainen J., Hannonen T., Pyhalahti T., Kamari J, Kallio K., Eloheimo K., Koponen S., 2001. Detection of water quality using simulated satellite data and semiempirical algorithms in Finland. The Science of the Total Environment, Elsevier, vol. 268, s. 107-121.
  • 9. Hedger R. D., Olsen N. R. B., Malthus T. J., Atkinson P. M., 2002. Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll-a concentration. Remote Sensing of Environment, vol. 79, s. 116-122.
  • 10. Heege T., Fischer J., 2004. Mapping of water constituents in Lake Constance using multispectral airborne scanner data and a physically based processing scheme. Canadian Journal of Remote Sensing, vol. 30, No. 1, 77-86.
  • 11. Kallio K., Kutser T., Hannonen T., Koponen S., Pulliainen J., Vepsalainen J., Pyhalahti T., 2001. Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons. The Science of the Total Environment, vol. 268, s. 59-77.
  • 12. Kloiber S. M., Brezonik P. L., Olmanson L. G., Bauer M. E., 2002. A procedure for regional lake water clarity assessment using Landsat mulispectral data. Remote Sensing of Environment, vol. 82, s. 38-47.
  • 13. Koponen S., Pulliainen J., Servomaa H., Zhang Y., Hallikainen M., Kallio K., Vepsalainen J., Pyhalahti T., Hannonen T., 2001. Analysis on the feasibility of multi-source remotesensing observations for chl-a monitoring in Finnish lakes. The Science of the Total Environment, vol. 268, s. 95-106.
  • 14. Koponen S., Pulliainen J., Kalliob K., Hallikainen M., 2002. Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, vol. 79, 51- 59.
  • 15. Lillesand T. M., Kiefer R. W., 1987. Remote Sensing and Image Interpretation. John Wiley & Sons.
  • 16. Lindell T., Rosengren M., 1981. Country-wide mapping of the water quality of Sweden using Landsat imagery. Colloque International du GDTA. La cartographie thématique des resultants de la télédétection, Toulouse, s. 408-416.
  • 17. Osińska-Skotak K., w przygotowaniu do druku. Metodyka wykorzystania super- i hiperspektralnych danych satelitarnych w analizie jakości wód śródlądowych. Rozprawa habilitacyjna. Wydział Geodezji i Kartografii, Politechnika Warszawska.
  • 18. Pierson D. C., Strömbeck N., 2000. A Modelling approach to evaluate preliminary remote sensing algorithms: use of water quality data from Swedish Great Lakes. Geophysica 36, 1-2, s. 177-202.
  • 19. Shafique N. A., Fulk F., Autrey B. C., Flotemersch J., 2003. Hyperspectral Remote Sensing of Water Quality Parameters for Lake Rivers in the Ohio River Basin. First Interagency Conference on Research in the Watershed, Benson, AZ, 27-30 October 2003, s. 216-221.
  • 20. Takio T., Vepsalainen J., Kaitala S., Fleming V., 2003. Remote sensing of chlorophyll-a in the Baltic Sea together with automated fluorometer measurements, ICES ASC– 2003, Thematic session L.
  • 21. Thiemann S., Kaufmann H., 2000. Determination of Chlorophyll Content and Trophic State of Lakes Using Field Spectrometer and IRS-1C Satellite Data in the Mecklenburg Lake District, Germany. Remote Sensing of Environment, vol. 73, s.227-235.
  • 22. Thiemann S., Kaufmann H., 2002. Lake water quality monitoring using hyperspectral airborne data – a semiempirical multisensor and multitemporal approach for the Mecklenburg Lake District, Germany. Remote Sensing of Environment, vol. 81, s. 228- 237.
  • 23. Yang M. D., Sykes R. M., Merry C. J., 2000. Estimation of algal biological parameters using water quality modeling and SPOT satellite data. Ecological Modelling, vol. 125, s. 1-13.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-821c1f50-63b1-4063-afc5-ddadea45b81b
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