[A-CG44] 静止軌道衛星による陸面観測

[ACG44-05] Advancing Geostationary Satellite Data Integration: Spectral Band Adjustment Using Hyperspectral Observations and Radiative Transfer Modeling

*笹川 大河¹、市井 和仁¹、山本 雄平¹、Wei Yang¹、松岡 真如²、吉岡 博貴³、Wang Weile⁴、Hashimoto Hirofumi⁴、奈佐原 顕郎⁵ (1.千葉大学、2.三重大学、3.愛知県立大学、4.NASAエイムズ研究所、5.筑波大学)

キーワード：静止衛星、データ融合、ハイパースペクトルデータ

Third-generation geostationary satellites, such as Japanese Himawari-8 and 9, the U.S. GOES series, Korean GK-2A, European MTG1, and Chinese Feng Yun-4, provide sub-hourly satellite observations that have significantly advanced Earth system monitoring. These hyper-temporal datasets are widely applied in ecosystem studies, particularly for vegetation monitoring, phenology analysis, gross primary production (GPP) estimation, and leaf area index (LAI) assessments using visible and near-infrared observations. However, due to the inherent orbital constraints of geostationary satellites, their coverage is regionally limited, posing challenges for global-scale data integration. To address this limitation, spectral band adjustments between different geostationary satellite sensors are essential. This study demonstrates a spectral band adjustment method that integrates 3D radiative transfer modeling with hyperspectral remote sensing data derived from both in situ and satellite observations. Our analysis revealed non-linear relationships between certain spectral bands across third-generation geostationary satellites. However, by leveraging vegetation indices, we successfully derived conversion equations to achieve a linear transformation, enabling seamless integration of hyper-temporal datasets across different satellite platforms. This approach enhances the consistency and comparability of geostationary satellite data, supporting global-scale Earth system monitoring.