Abstract
Submersed aquatic vegetation (SAV) is sensitive to changes in environmental conditions and plays an important role as a long-term indictor for the trophic state of freshwater lakes. Variations in water level height, nutrient condition, light availability and water temperature affect the growth and species composition of SAV. Detailed information about seasonal variations in littoral bottom coverage are still unknown, although these effects are expected to mask climate change-related long-term changes, as derived by snapshots of standard monitoring methods included in the European Water Framework Directive. Remote sensing offers concepts to map SAV quickly, within large areas, and at short intervals. This study analyses the potential of a semi-empirical method to map littoral bottom coverage by a multi-seasonal approach. Depth-invariant indices were calculated for four Atmospheric & Topographic Correction (ATCOR2) atmospheric corrected RapidEye data sets acquired at Lake Kummerow, Germany, between June and August 2015. RapidEye data evaluation was supported by in situ measurements of the diffuse attenuation coefficient of the water column and bottom reflectance. The processing chain was able to differentiate between SAV and sandy sediment. The successive increase of SAV coverage from June to August was correctly monitored. Comparisons with in situ and Google Earth imagery revealed medium accuracies (kappa coefficient = 0.61, overall accuracy = 72.2%). The analysed time series further revealed how water constituents and temporary surface phenomena such as sun glint or algal blooms influence the identification success of lake bottom substrates. An abundant algal bloom biased the interpretability of shallow water substrate such that a differentiation of sediments and SAV patches failed completely. Despite the documented limitations, mapping of SAV using RapidEye seems possible, even in eutrophic lakes.
Highlights
Monitoring submersed aquatic vegetation (SAV) is important, since occurrence and species composition are long-term indicators for the trophic state of freshwater ecosystems [1]
The results further demonstrated that Rapid Eye was able to map seasonal changes in SAV coverage
Water constituents derived from in situ taken samples [suspended particulate material (SPM), chlorophyll a (Chl a), absorption by coloured dissolved organic matter] and Secchi depths varied for acquisition dates
Summary
Monitoring submersed aquatic vegetation (SAV) is important, since occurrence and species composition are long-term indicators for the trophic state of freshwater ecosystems [1]. To detect changes at an early stage, Palmer et al [10] recommended more frequent observations of freshwater lakes. Remote sensing provides time- and cost-effective methods to observe seasonal and annual changes in water quality and macrophyte coverage [11,12,13,14,15,16,17,18,19]. Palmer et al [10] concluded that changes in SAV covered areas can be detected by recently available remote sensing systems that are well suited to complement regular in situ sampling, as required by the WFD. High revisiting time and broad coverage of shallow lakeshore areas of remote sensing data may compensate for the reduced information on species compared to mappings
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