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

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 concentrat...

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Bibliographic Details
Published in:Journal of limnology 2019-01, Vol.78 (1), p.71-91
Main Authors: Fritz, C, Kuhwald, K, Schneider, T, Geist, J, Oppelt, N
Format: Article
Language:English
Subjects:
Aquatic ecosystems
Aquatic plants
bio-optical modelling
Bioindicators
depth-invariant index
Environmental changes
Freshwater
Freshwater ecosystems
Freshwater lakes
Freshwater weeds
Growing season
Growth
Growth rate
Indicator organisms
Indicator species
Inland water environment
Lakes
Mapping
Methods
monitoring inland waters
Nutrient availability
Nutrient concentrations
Plant cover
Reflectance
Remote sensing
Shallow water
Simulators
Species composition
submerse aquatic vegetation
Trophic state
Trophic structure
Vegetation
Water colour
Water depth
Water temperature
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Summary: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
ISSN:1129-5767
1723-8633
DOI:10.4081/jlimnol.2019.1824