HUMBOLDT UNIVERSITAT ZU BERLIN (DE)
Quality and quantity of current high resolution optical earth observation data is unprecedented and provides an opportunity to advance remote sensing land system analyses. However, cloud coverage and a lack of gridded higher level products still hampers the widespread usability of the data. This research addresses these shortcomings by developing toolsets to combine data streams from Sentinel-2 and Landsat-8 and that allow for the systematic (i.e. weekly, monthly, seasonal-) generation of composited reflectance and subsequently value-added products (e.g. percent cover estimates, annual phenology metrics). This suite of generated products will be synergetically exploited in order to address higher level land-use science questions that cannot readily be answered using spectral data only. While methods are developed to be capable of working with most ecosystems, a specific focus is on improving agricultural mapping and analyses.
