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

Dörnhöfer, K., Scholze, J., Stelzer, K. and Oppelt, Natascha (2018) Water Colour Analysis of Lake Kummerow Using Time Series of Remote Sensing and In Situ Data. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86 (2). pp. 103-120. DOI 10.1007/s41064-018-0046-3.

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Supplementary data:

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
mg
m
−3
)
mgm−3)
exhibited a spring bloom and multiple blooms during summer. Total suspended matter (0.1–10.0
g
m
−3
)
gm−3)
and coloured dissolved organic matter (0.01–0.94
m
−1
)
m−1)
revealed highest values during summer and lower values during autumn/winter. While total suspended matter (− 1.3
g
m
−3
)
gm−3)
and chlorophyll-a (− 3.4
mg
m
−3
)
mgm−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.

Document Type: Article
Keywords: Inland Waters, Seasonality, Spatial Patterns, Trend analysis
Research affiliation: Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Kiel University
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1007/s41064-018-0046-3
ISSN: 2512-2789
Date Deposited: 17 Apr 2019 12:16
Last Modified: 21 Jun 2019 11:53
URI: http://oceanrep.geomar.de/id/eprint/46395

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