[A-CG36] Satellite Earth Environment Observation

[ACG36-01] Challenges toward hyper-temporal monitoring of terrestrial vegetation using 3rd generation geostationary satellites, Himawari-8/9

*Kazuhito Ichii¹, Yuhei Yamamoto¹, Wei Li¹, Beichen Zhang¹, Misaki Hase¹, Shibayama Reo¹, Shogo Sumii¹ (1.Chiba University)

Keywords:geostationary satellites, terrestrial vegetation, carbon cycle, drought monitoring

Third-generation geostationary meteorological satellites, such as Himawari 8/9, are capable of making observations as frequently as once every 10 minutes, and are characterized by having multiple observation wavelength bands in the visible and near-infrared regions compared to conventional geostationary satellites. In addition, they have improved spatial resolution and observation frequency, including the thermal infrared band. The visible and near-infrared wavelength bands are similar to those of sensors onboard polar-orbiting satellites (MODIS, SGLI, etc.), which are widely used for land surface observations. It is possible to observe land surfaces at a higher frequency than conventional polar-orbiting satellites. Therefore, they are expected to be applied to monitoring changes in the terrestrial environment, such as vegetation and land cover. In this presentation, we will introduce our efforts to monitor the land surface and vegetation using data from Himawari and other countries' geostationary meteorological satellites. On the other hand, in order to apply geostationary meteorological satellite data to land area monitoring, it is necessary to calculate and verify surface reflectance. In this presentation, I will introduce the following efforts and results on the advancement of land surface monitoring by geostationary meteorological satellites: (1) the plan and progress of data products in our group, (2) increasing cloud-free data by improving the frequency of observations to more accurately determine the vegetation phenology, (3) detecting vegetation phenology in tropical rainforest areas that have been difficult to observe by satellite due to cloud cover, (4) rapid identification of water stress conditions of vegetation using 10-minute changes in surface temperature, (5) early detection of water stress conditions of vegetation through observations at 10-minute intervals, and (6) establishing an international observation and collaboration network.