Evaluation of common reed (Phragmites australis) bed changes in the context of management using earth observation and automatic threshold

Abstract

There is no easy in situ way to monitor large waterbodies for their aquatic vegetation change, especially during mowing works. The objective of this study is to choose the best automatic workflow that would estimate a change in the reed bed area and density over time. This workflow will assess the mowing effect on reeds over 3 years in the Plateliai Lake (Lithuania). Sentinel-2/MSI images were used to derive reed beds using water adjusted vegetation index (WAVI) and normalised difference water index (NDWI). The indices were classified using seven different binary thresholding algorithms. Results were validated with orthophotos gathered from unmanned aerial vehicle surveys in mowed regions and one reference area. Analysis demonstrated that using the NDWI together with the Yen thresholding algorithm generated the best accuracy results, with the highest accuracy resulting with high vegetation areas where the area under the curve values were 0.85 ± 0.17. The changes in estimated density did not show a significant correlation between mowed and reference areas and years. The results indicate that Sentinel-2/MSI is a feasible tool for the evaluation of reed bed change. On this basis, it is recommended to implement it as an additional monitoring tool that covers larger areas than in situ monitoring.