EGU24-4848, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Global Civil Earth Observation Satellite Semantic Database

Ming Lin1, Meng Jin1, Juanzi Li2, and Yuqi Bai1
Ming Lin et al.
  • 1Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, China
  • 2Department of Computer Science and Technology, Tsinghua University, Beijing, China

The advancement of satellite remote sensing technology has transformed our capacity to monitor and address global challenges. This technology provides global coverage, frequent observation revisits, and consistent monitoring, thus providing critical data support. Since the first Earth observation satellite was launched in the 1960s, more than a thousand Earth observation satellites have been deployed by various countries and organizations. However, the substantial accumulation of Earth observation assets is maintained independently by different organizations using varying methodologies. This poses a significant challenge in effectively utilizing and maximizing the value of these global observation resources.

This study introduces GEOSatDB, a comprehensive semantic database specifically tailored for civil Earth observation satellites. The foundation of the database is an ontology model conforming to standards set by the International Organization for Standardization (ISO) and the World Wide Web Consortium (W3C). This conformity enables data integration and promotes the reuse of accumulated knowledge. Our approach advocates a novel method for integrating Earth observation satellite information from diverse sources. It notably incorporates a structured prompt strategy utilizing a large language model to derive detailed sensor information from vast volumes of unstructured text.

To demonstrate the capabilities of GEOSatDB, we performed a comprehensive analysis of the distribution of Earth observation satellites in 195 countries. This analysis unveiled the global distribution and diversity of these assets. Furthermore, two distinct case studies showcase the practical application and robust data mining potential of GEOSatDB. With information on 2,340 remote sensing satellites and 1,018 sensors, this database represents a significant advancement in semantically sharing and applying Earth observation resources. Its establishment encourages enhanced international cooperation and more efficient environmental monitoring and management.

How to cite: Lin, M., Jin, M., Li, J., and Bai, Y.: Global Civil Earth Observation Satellite Semantic Database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4848,, 2024.

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