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Water Colour Analysis of Lake Kummerow Using Time Series of Remote Sensing and In Situ Data

  • K. Dörnhöfer
  • J. Scholze
  • K. Stelzer
  • N. Oppelt
Original Article

Abstract

Monitoring water constituents of lakes using satellites is gaining increasing importance. Image archives of historic satellites represent valuable data sources to analyse the development of constituent concentrations over time and to derive trends. This study presents an analysis of the MERIS archive (2003–2011) using a neural network algorithm (FUB/WeW) to retrieve concentrations of Chlorophyll-a, total suspended matter and absorption by coloured dissolved organic matter (440 nm) at Lake Kummerow. All three constituents showed a clear seasonality: Chlorophyll-a (0.3–45.8 \(\hbox {mg}\,\hbox {m}^{-3})\) exhibited a spring bloom and multiple blooms during summer. Total suspended matter (0.1–10.0 \(\hbox {g}\,\hbox {m}^{-3})\) and coloured dissolved organic matter (0.01–0.94 \(\hbox {m}^{-1})\) revealed highest values during summer and lower values during autumn/winter. While total suspended matter (− 1.3 \(\hbox {g}\,\hbox {m}^{-3})\) and chlorophyll-a (− 3.4 \(\hbox {mg}\,\hbox {m}^{-3})\) showed a decreasing tendency from 2003 to 2011, coloured dissolved organic matter showed no clear trend. Chlorophyll-a retrieved from MERIS was around 20% higher than in situ measurements. The other constituents (total suspended matter and coloured dissolved organic matter) were obtained by qualitative analysis due to the absence of in situ measurements. This analysis provides a first multi-year time series on these constituents over the whole lake and all seasons. Both, its size and its form, make Lake Kummerow a suitable lake for remote sensing validation activities. Recent and upcoming satellites, especially of the Sentinel missions, will provide further valuable information for integrating remote sensing into lake monitoring.

Keywords

Inland waters Seasonality Spatial patterns Trend analysis 

Zusammenfassung

Analyse der Wasserfarbe des Kummerower Sees unter Verwendung von Zeitreihen von Fernerkundungsdaten und in situ Daten.

Das Monitoring von Wasserinhaltsstoffen in Seen mithilfe von Satellitendaten gewinnt zunehmend an Bedeutung. Die Bildarchive historischer Satelliten stellen wertvolle Datenquellen dar, um einen Eindruck von der zeitlichen Entwicklung der Konzentrationen zu gewinnen. Diese Studie umfasst eine Analyse des MERIS-Archivs (2003 – 2011) unter Verwendung eines neuronalen Netzwerk-Algorithmus (FUB/WeW), um die Konzentrationen von Chlorophyll-a, suspendierten Schwebstoffen und die Absorption gelöster organischer Stoffe (440 nm) am Kummerower See zu bestimmen. Alle drei Wasserinhaltsstoffe zeigten eine klare Saisonalität: Chlorophyll-a-Gehalte (0,3 \(\hbox {mg}\,\hbox {m}^{-3 }\)– 45,8 \(\hbox {mg}\, \hbox {m}^{-3})\) wiesen auf eine deutliche Frühjahrsblüte und mehrere Algenblüten im Sommer hin. Die suspendierten Schwebstoffe (0,1 \(\hbox {g}\,\hbox {m}^{-3}\) – 10,0 \(\hbox {g}\,\hbox {m}^{-3})\) und gelösten organische Stoffe (0,01 \(\hbox {m}^{-1 }\)– 0,94 \(\hbox {m}^{-1})\) erreichten im Sommer die höchsten und im Herbst/Winter die niedrigsten Werte. Suspendierte Schwebstoffe (-1,3 \(\hbox {g}\,\hbox {m}^{-3})\) und Chlorophyll-a (-3,4 \(\hbox {mg}\,\hbox {m}^{-3})\) tendierten von 2003–2011 zu einer leichten Abnahme, die gelösten organischen Stoffe zeigten keinen klaren Trend. Die Chlorophyll-a Ableitung über MERIS war im Vergleich zu insitu Messungen etwa 20% höher. Die anderen Wasserinhaltsstoffe (suspendierte Schwebstoffe und gelöste organische Stoffe) wurden qualitativ ausgewertet. Diese Analyse stellt eine erste Zeitreihe über den gesamten See und zu allen Jahreszeiten dar. Die Größe und Form des Kummerower Sees machen ihn zu einem geeigneten See für die Validierung von Fernerkundungsansätzen. Aktuelle und zukünftige Satelliten, insbesondere der Sentinel-Missionen, werden weitere wertvolle Informationen liefern, um die Fernerkundung in das Seenmonitoring zu integrieren.

Schlüsselwörter

Binnengewässer Saisonalität Räumliche Muster Trendanalyse 

Notes

Acknowledgements

This work was conducted within the project LAKESAT (Grant no: 50EE1340) funded by the Federal Ministry for Economic Affairs and Energy, Germany. We acknowledge the Mecklenburg-Vorpommern Ministry for Agriculture, Environment and Consumer Protection for data supply from the lake monitoring programme. Many thanks are due to ESA for providing MERIS data.

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Copyright information

© Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation (DGPF) e.V. 2018

Authors and Affiliations

  1. 1.Department of Geography, Earth Observation and ModellingChristian-Albrechts-Universität zu KielKielGermany
  2. 2.Brockmann Consult GmbHGeesthachtGermany

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