Fast and Unified Earth Observation Data Exploration to Optimize Value-adding and Climate-positive Applications

Although an increasing number of services relies on Earth Observation (EO) information, the identification of possibly interesting data is still an obscure and elaborate task. Consequently, most value-adding services use only a fraction of the EO data available and rely on few well-known, public data sources as for instance from the Sentinel or Landsat missions. However, especially more data from various sensors, reduces effective revisiting times and translates into actionable insights of increased value. Therefore, the Fraunhofer Institute for High-Speed Dynamics (EMI) developed a Coverage Planning Tool (CPT) to minimize the complexity of identifying suitable EO data, close gaps in previously missing data, increase market transparency and thus, considerably reduce entry barriers for new applications or help to create improved research results. In general, CPT is based on two components. First, a computational core based on a patented methodology for rapid sensor contact assessments, to quickly determine the sensor coverage of hundreds of sensors for a given set of coordinates in the past as well as in the future. Second, an extensive database that includes a comprehensive and up-to-date list of EO platforms from major free and commercial providers with all relevant sensor characteristics. Together, both components enable CPT to explore EO data in a fast and unified way. The Coverage Planning Tool has been successfully implemented in a Fast and Intuitive Data Retrieval (FINDR) platform developed to support Value Added Service Providers in the agricultural sector. Based on CPT, FINDR offers to rapidly discover all available EO data for a cultivated area of interest over the duration of the growing season, create an extensive resource plan in addition to optionally identify critical data gaps that can be closed by an implemented homogenization approach.