Atmospheric and Hydrospheric Sciences (A)
Session Sub-category Complex & General(CG)
Session ID A-CG44
Title Terrestrial monitoring using geostationary satellites
Short Title Terrestrial monitoring by GEO satellites
Main Convener Name Yuhei Yamamoto
Affiliation Center for Environmental Remote Sensing, Chiba University
Co-Convener 1 Name Tomoaki Miura
Affiliation Univ Hawaii
Co-Convener 2 Name Kazuhito Ichii
Affiliation Chiba University
Session Language 
E
Scope 
With the launch of third-generation geostationary satellites, such as Himawari-8/9, the GOES-R series, Meteosat Third Generation (MTG), Fengyun-4, and GeoKompsat-2A, Earth observation has entered a new phase. These satellites carry advanced sensors with spectral bands suitable for terrestrial monitoring, similar to those on polar-orbiting satellites. They enable high-frequency (e.g., 10-minute) monitoring of key land parameters, including land surface temperature/albedo, vegetation indices, evapotranspiration, and photosynthetic activity. Combining data from these geostationary satellites with data from polar-orbiting satellite sensors like Terra/Aqua MODIS, Suomi NPP/NOAA-20 VIIRS, and GCOM-C SGLI makes global, consistent land monitoring possible.
This session invites presentations on methods for estimating land surface parameters using these geostationary and polar-orbiting satellites, as well as efforts in inter-calibration and cross-validation using GEO and LEO data. We welcome studies on in-situ validation efforts and new applications of these datasets for monitoring and understanding various phenomena, such as heatwaves, drought, and long-term climate change impacts. Additionally, studies on atmospheric factors, such as cloud cover and aerosols, and their influence on land surface conditions are also highly encouraged.
Presentation Format Oral and Poster presentation
Time Presentation No Title Presenter
Oral Presentation May 28 AM1
9:15 - 9:30 ACG44-01 An Open Dataset for Hypertemporal Land Surface Monitoring via Geostationary Meteorological Satellites and Its Applications Kazuhito Ichii
9:30 - 9:45 ACG44-02 High-Temporal-Resolution Land Surface Albedo Estimation Using Himawari-8/9 AHI: Evaluation with In-Situ and MODIS Observations Wei Li
9:45 - 10:00 ACG44-03 A Hyper-temporal Monitoring of Terrestrial Evapotranspiration Using Himawari-8 Satellite Beichen Zhang
10:00 - 10:15 ACG44-04 Geostationary-Satellite-Based Study of Diurnal Variation in Aerosol-Cloud Interactions Hengqi Wang
Oral Presentation May 28 AM2
10:45 - 11:00 ACG44-05 Advancing Geostationary Satellite Data Integration: Spectral Band Adjustment Using Hyperspectral Observations and Radiative Transfer Modeling Taiga Sasagawa
11:00 - 11:15 ACG44-06 Development of a rice crop calendar estimation algorithm from Himawari satellite imagery Kazuya Nishina
11:15 - 11:30 ACG44-07 Exploring the optimal geometry of Himawari-8/9 to monitor vegetation dynamics across Southeast Asia Misaki Hase
11:30 - 11:45 ACG44-08 Reduction of Snow Contamination in Himawari-8/-9 AHI NDVI for Improved Phenology Monitoring Tomoaki Miura
11:45 - 12:00 ACG44-09 Post-Typhoon Extreme Heat Events: Land Surface Temperature Variability and Urban Land Use Influences Yuhei Yamamoto
Presentation No Title Presenter
Poster Presentation May 28 PM3
ACG44-P01 Monitoring and Analysis of Atmospheric Gravity Wave Horizontal Propagation Using Thermal Satellite Imagery from Himawari-8/9 Thanaphat Lertmongkhon
ACG44-P02 Determining Vegetation Critical Temperature Thresholds in Australia Using Himawari-8/9 LST data Reo Shibayama
ACG44-P03 Retrieval of the Vegetation Clumping Index (CI) from Geostationary Satellite Observations Using an Improved BRDF Model ZHI QIAO
ACG44-P04 Spatiotemporal variability of land surface temperature in Southeast Asia’s Megacities using geostationary satellites, Himawari-8/9 Soma Yamasaki
ACG44-P05 Investigation of surface changes in Tsambagarav National Park using summer Landsat normalized difference spectral indices Mei Matsubara
ACG44-P06 A new vegetation monitoring method using geostationary satellite data based on a kernel-driven BRDF model Yueru Wen