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After an extreme flood in Lake Constance in 1999 the Phragmites australis belt showed a severe decline in area and vitality. A three year monitoring project was installed in 2000 to document the die-back and rehabilitation process immediately afterwards, to identify the co-factors of the damage, and to find out significant stressors that may impede the recovery of the reeds. The monitoring is based on CIR aerial photo interpretation, quantitative GIS analyses and field investigations on shoot density, stand structure and biomass production in 50 monitoring plots, grouped in five degrees of damage. In result we found that c. 0.306 km 2 of aquatic reed bed area died back at Lake Constance-Untersee (i.e. 23% of the former area in 1998). Among the stands which had survived the severely damaged stands were mainly composed of secondary shoots, whereas primary and insect infested shoots dominated in less damaged stands. The development from 2000 to 2001 was characterized by an overall decrease in shoot density, a change in the composition of the shoot population in favour of primary shoots, and in a recovery in culm stature. All variables depended on the degree of initial damage by the extreme flood. A conceptual model is proposed to assess the future development of Lake Constance reeds.

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Physics-based remote sensing in littoral environments for ecological monitoring and assessment is a challenging task that depends on adequate atmospheric conditions during data acquisition, sensor capabilities and correction of signal disturbances associated with water surface and water column. Airborne hyper-spectral scanners offer higher potential than satellite sensors for wetland monitoring and assessment. However, application in remote areas is often limited by national restrictions, time and high costs compared to satellite data. In this study, we tested the potential of the commercial, high-resolution multi-spectral satellite QuickBird for monitoring littoral zones of Lake Sevan (Armenia). We present a classification procedure that uses a physics-based image processing system (MIP) and GIS tools for calculating spatial metrics. We focused on classification of littoral sediment coverage over three consecutive years (2006)(2007)(2008) to document changes in vegetation structure associated with a rise in water levels. We describe a spectral unmixing algorithm for basic classification and a supervised algorithm for mapping vegetation types. Atmospheric aerosol retrieval, lake-specific parameterisation and validation of classifications were supported by underwater spectral measurements in the respective seasons. Results revealed accurate classification of submersed aquatic vegetation and sediment structures in the littoral zone, documenting spatial vegetation dynamics induced by water level fluctuations and interannual variations in phytoplankton blooms. The data prove the cost-effective applicability of satellite remote-sensing approaches for high-resolution mapping in space and time of lake littoral zones playing a Guest editor: Martin A. Stapanian / QuickBird satellite imagery as a tool for restoration and rehabilitation of Lake Sevan, Armenia