[A-CG36] Terrestrial monitoring using new-generation geostationary satellites

[ACG36-07] Prototyping the Chinese FengYun Geostationary Environmental Monitoring System (FEMS-Geo) for hyper-temporal applications

★Invited Papers

*Xuanlong Ma¹ (1.Lanzhou University)

Keywords:hyper-temporal, Fengyun, geostationary, environmental monitoring, biogeosciences

Current environmental monitoring systems are primarily based on polar-orbiting satellites with low revisit frequency that can miss important land and atmospheric phenomenon such as landslides or diurnal land-atmosphere mass and energy exchanges. A new generation of geostationary (GEO) satellites is now being putting into the orbit, including Himawari-8 (Japan), FengYun (FY)-4 (China), Geo-KOMPSAT-2A (Korea), and Geostationary Operational Environmental Satellite (GOES)-16/17 (USA), all with high spatial, radiometric and temporal resolutions. For instance, the Chinese FY-4A/B geostationary satellites, launched in 2015 and 2021 respectively, carries an Advanced Geostationary Radiation Imager (AGRI) that has spectral bands similar to MODIS. FY4/AGRI scans the full disk (Asia-Oceania region) at 15-minute intervals and generates 96 images each day. The data from FY4/AGRI, alongside other GEO satellites, therefore, offer unprecedented opportunities for environmental monitoring tasks such as vegetation change, landslides, urban heat island, air quality, and flooding with much improved time-domain information. To fully exploit the potentials from the new generation GEO satellites, in collaboration with the Chinese National Satellite Meteorology Center and other international institutions, we are developing FengYun Geostationary Environmental Monitoring System (FEMS-Geo) that can efficiently ingest the hyper-temporal information to generate user-friendly scientific outputs. The FEMS-Geo system consists of three major functional units: 1) a data processing unit including the corrections of geometric, topographic, atmospheric, angular effects as well as the cloud detection; 2) a science products generation unit including the retrieval algorithms for vegetation index, land surface phenology, gross primary productivity, land surface temperature, evapotranspiration and so on; 3) a high-performance computation unit that including data streaming and archiving, data preprocessing and retrieving, as well as scientific product publishing. The overarching aim is to facilitate the end-users in China and surrounding regions for their specific applications by leveraging the hyper-temporal FY4 data.