Analysing the potential of multispectral sensors to map vegetation parameters in pre-Alpine and Alpine grasslands

Kurzfassung

Pastures and natural grasslands are an important part of the pre-Alpine and Alpine landscape ranging from intensive grasslands in the lower regions to highly diverse seasonal mountain pastures and specialized natural ecosystems. Despite the economic value and the significant role of plants in grassland carbon (C) and nitrogen (N) cycling, spatially explicit information on grassland management and yields (biomass and quality) are rarely available. Within the SUSALPS project, we aim to use new Copernicus satellite data to derive spatially explicit information (maps) on grassland management and biomass production, including cutting frequencies and plant N contents. Satellite remote sensing will be complemented by unmanned aerial vehicle (UAV)-based data acquisition to better bridge the scale gap from field measurements to regional assessment, and to validate satellite-derived products on larger scales. In April 2018, we conducted a field campaign to investigate the potential to map biomass, leaf N content, and other vegetation parameters with two different UAV-based multispectral sensors (Parrot SEQUOIA; RedEdge-M by MicaSense). Data over ten different grassland sites in southern Bavaria was collected via UAV and field sampling (destructive and proximal sensing) and will be analyses for correlations between different multispectral bands/indices and vegetation parameters. This contribution will present the sampling design and first results of the field experiment.