Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes

Semi-analytical remote sensing applications for eutrophic waters are not applicable to oligo- and mesotrophic lakes in the perialpine area, since they are insensitive to chlorophyll concentration variations between 1 and 10 mg/m 3. The neural network based Case-2-Regional algorithm for MERIS was dev...

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Bibliographic Details
Published inRemote sensing of environment Vol. 114; no. 3; pp. 607 - 617
Main Authors Odermatt, Daniel, Giardino, Claudia, Heege, Thomas
Format Journal Article
LanguageEnglish
Published New York, NY Elsevier Inc 15.03.2010
Elsevier
Subjects
Algorithms
Animal, plant and microbial ecology
Applied geophysics
Biological and medical sciences
Chlorophylls
Collection
Earth sciences
Earth, ocean, space
Exact sciences and technology
Freshwater
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Inland water
Internal geophysics
Lakes
Monitoring
Neural networks
Remote sensing
Teledetection and vegetation maps
Temporal logic
Time series
Water constituents
Water quality
Lakes
Water constituents
Inland water
Monitoring
Water quality
Time series
experimental studies
algorithms
data
springs
neural networks
Result
Site specificity
2008
collections
2003
variations
lakes
Constituent
testing
chlorophyll
Satellite observation
remote sensing
concentration
monitoring
in situ
corrections
water quality
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Summary:Semi-analytical remote sensing applications for eutrophic waters are not applicable to oligo- and mesotrophic lakes in the perialpine area, since they are insensitive to chlorophyll concentration variations between 1 and 10 mg/m 3. The neural network based Case-2-Regional algorithm for MERIS was developed to fill this gap, along with the ICOL adjacency effect correction algorithm. The algorithms are applied to a collection of 239 satellite images from 2003–2008, and the results are compared to experimental and official water quality data collected in six perialpine lakes in the same period. It is shown that remote sensing estimates can provide an adequate supplementary data source to in situ data series of the top 5 m water layer, provided that a sufficient number of matchups for a site specific maximum temporal offset are available.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2009.10.016