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The suitability of using Landsat TM-5 Images for estimating chromophoric dissolved organic matter in subarctic Lakes
Responsible organisation
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Recent trends of permafrost thawing in the subarctic are expected to cause increased release of dissolved organic carbon (DOC) to inland waters, which might have cascading effects on downstream aquatic ecosystems and release of CO2 to the atmosphere. This study therefore aimed at evaluating the applicability of an empirical band ratio algorithm for estimating chromophoric dissolved organic matter (CDOM; a proxy for DOC) from the easily accessible satellite images Landsat TM-5, to counter the inaccessibility of the region in general. The study targeted 14 smaller lakes in the Stordalen catchment in northern Sweden where values of CDOM absorbance had been obtained from the summer of 2009 that could be used to evaluate algorithm suitability. The satellite image type and algorithm have been successfully applied to predict CDOM in previous studies of lakes with relatively high absorbance, but in this study no significant correlations were found between the in situ measured and the remote sensing estimates for the studied lakes (in situ aCDOM (440) = 0.29 - 1.22 m-1; R2 ≀ 0.21); except for when lakes with certain characteristics were tested separately (shallow lakes R2 = 0.86). It was concluded that Landsat TM-5 images are not generally suitable for estimating CDOM in the Stordalen area. However higher quality satellite products probably would; since with a higher ground-, spectral- and radiometric resolution some disturbances could be reduced, more lakes could be included in the study and they would be more accurately recorded. Nonetheless more in situ collected data is needed for supporting the discussed deductions and for adaptive algorithm modifications.

Place, publisher, year, edition, pages
2014.
Series
Student thesis series INES ; 299
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:polar:diva-4227OAI: oai:DiVA.org:polar-4227DiVA, id: diva2:1178764
Note

Student Paper

Available from: 2018-01-30 Created: 2018-01-30 Last updated: 2018-01-30Bibliographically approved

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  • apa
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  • de-DE
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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