Sentinel-2 for mapping the spatio-temporal development of submerged aquatic vegetation at Lake Starnberg (Germany)

Mapping the spatial distribution of submerged aquatic vegetation

  • Christine Fritz | christine.fritz@mytum.de Aquatic Systems Biology Unit, Limnological Research Station Iffeldorf, Department of Ecology and Ecosystem Management, Technical University of Munich, Germany.
  • Katja Kuhwald Earth Observation and Modelling, Department of Geography, Christian-Albrechts-Universität zu Kiel, Germany.
  • Thomas Schneider Aquatic Systems Biology Unit, Limnological Research Station Iffeldorf, Department of Ecology and Ecosystem Management, Technical University of Munich, Germany.
  • Juergen Geist Aquatic Systems Biology Unit, Limnological Research Station Iffeldorf, Department of Ecology and Ecosystem Management, Technical University of Munich, Germany.
  • Natascha Oppelt Earth Obersvation and Modelling, Department of Geography, Christian-Albrechts-Universität zu Kiel, Germany.

Abstract

Submerged aquatic vegetation (SAV) plays an important role in freshwater lake ecosystems. Due to its sensitivity to environmental changes, several SAV species serve as bioindicators for the trophic state of freshwater lakes. Variations in water temperature, light availability and nutrient concentration affect SAV growth and species composition. To monitor the trophic state as required by the European Water Framework Directive (WFD), SAV needs to be monitored regularly. This study analyses the development of macrophyte patches at Lake Starnberg, Germany, by exploring four Sentinel-2A acquired within the main growing season in August and September 2015. Two different methods of littoral bottom coverage assessment are compared, i.e. a semi-empirical method using depth-invariant indices and a physically based, bio-optical method using WASI-2D (Water Colour Simulator). For a precise Sentinel-2 imaging by date and hour, satellite measurements were supported by lake bottom spectra delivered by in situ data based reflectance models. Both methods identified vegetated and non-vegetated patches in shallow water areas. Furthermore, tall- and meadow-growing SAV growth classes could be differentiated. Both methods revealed similar results when focusing on the identification of sediment and SAV patches (R² from 0.56 to 0.81), but not for a differentiation on SAV class growth level (R² <0.42).

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Published
2019-01-02
Section
Original Articles
Edited by
Mariano Bresciani, CNR-IREA, Milan, Italy
Supporting Agencies
Federal Ministry for Economic Affairs and Energy (grants 50EE1336 and 50EE1340), Limnological Research Station Iffeldorf, German Research Foundation (DFG), Technical University of Munich within the funding programme Open Access Publishing
Keywords:
Remote sensing, Sentinel-2, submerse aquatic vegetation, inland waters monitoring, depth-invariant index, bio-optical modelling
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How to Cite
1.
Fritz C, Kuhwald K, Schneider T, Geist J, Oppelt N. Sentinel-2 for mapping the spatio-temporal development of submerged aquatic vegetation at Lake Starnberg (Germany). jlimnol [Internet]. 2Jan.2019 [cited 29Jan.2020];78(1). Available from: https://jlimnol.it/index.php/jlimnol/article/view/jlimnol.2019.1824