| Project/Area Number |
15H02856
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Environmental and ecological symbiosis
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| Research Institution | Aichi Prefectural University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
松岡 真如 高知大学, 教育研究部自然科学系農学部門, 准教授 (50399325)
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| Research Collaborator |
OBATA Kenta
TANIGUCHI Kenta
MIURA Munenori
ADACHI Yusuke
KIKUCHI Ryota
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥8,710,000 (Direct Cost: ¥6,700,000、Indirect Cost: ¥2,010,000)
Fiscal Year 2018: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2017: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2016: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2015: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | リモートセンシング / 地球観測 / Himawari8 / AHI / MODIS / アイソライン / 放射伝達モデル / Terra / 自然現象観測・予測 / 人工衛星 / 計算工学 / 計測工学 / 事前現象観測・予測 |
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| Outline of Final Research Achievements |
This study discusses three fundamental factors that induce relative errors in data from Earth observation satellites: spatial resolution, observation geometry, and observation wavelength. The study sought to clarify how these factors influence the intersensor relationship of data products at higher processing levels. In the first half of this study, relationships between two reflectances of different wavelengths were derived. In the second half, the derived relationships were refined to relate spectral vegetation indices (VIs) obtained from two distinct satellite sensors. As a result, a set of analytical formulae were obtained that can be used for standardizing VI data between pairs of sensors.
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| Academic Significance and Societal Importance of the Research Achievements |
人工衛星による地球観測手法は地球全体の環境を長期にわたり把握し，気候変動メカニズムの解明に資する情報を得る手段の１つである．各国研究機関が進めてきた観測プロジェクトは，膨大な量と種類のデータセットの蓄積に繋がった．一方，これらのデータセットは仕様の異なるセンサで観測されたものであり，90年代後半にはデータセット間の連続性および一貫性の重要性が指摘され始めた．本研究の学術的な意義はこれらセンサ仕様差に起因するデータセット間のギャップを埋め蓄積データ全体の精度を高めることに貢献する点にある．観測データの一貫性を高めることは，健全な地球環境の維持に資する取り組みの１つである．
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