Quality and quantity of current high-resolution optical Earth observation data is unprecedented and provides an opportunity to advance remote sensing-based land systems analyses. However, cloud coverage and a lack of gridded higher-level products still hampers the widespread usability of such data. This research project addressed these shortcomings by developing toolsets to combine data streams from ESA Sentinel-2 and USGS/NASA Landsat-8. It for the first time allowed for the systematic (i.e. weekly, monthly, seasonal-) generation of composited reflectance and downstream value-added products (e.g. percent cover estimates, annual phenology metrics). These novel integrated time-series were for the first time synergistically exploited to address land-use science questions related to agricultural land use and land use intensity that can only be answered when using dense time-series based on wall-to-wall analyses at 10-30m spatial resolution. While methods were developed to be capable of working with most ecosystems, a specific focus is on improving agricultural mapping and analyses. We specifically focused on crop type mapping and grassland use intensity.