| Project/Area Number |
18H01924
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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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| Review Section |
Basic Section 31020:Earth resource engineering, Energy sciences-related
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
柏谷 公希 京都大学, 工学研究科, 准教授 (40447074)
後藤 忠徳 兵庫県立大学, 生命理学研究科, 教授 (90303685)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2020: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2019: ¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2018: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
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| Keywords | リモートセンシング / 衛星画像 / ダウンスケーリング / 地質マッピング / 資源探査 / 反射スペクトル / 短波長赤外域 / 空間分解能 |
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| Outline of Final Research Achievements |
This study has developed a joint downscaling method of both spectral and spatial resolutions to clarify mineral distributions related to generation of metal and geothermal resources in detail by transforming satellite multispectral imagery (MS) to hyperspectral imagery (HP). Spectral downscaling was achieved accurately by correlating reflectances between MS and HP images with the generalized additive model of multivariate analysis. Moreover a radiance division method was developed for the spatial downscaling based on a criterion of the correspondence in radiance at a same location on low- and high-resolution images. These two methods were applied to ASTER scene images, a representative MS satellite imagery covering areas of cupper and gold deposits and geothermal manifestations, and their effectiveness was demonstrated because typical hydrothermal alteration minerals such as kaolinite and muscovite were discriminated and mapped with high accuracy around the deposits and manifestations.
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| Academic Significance and Societal Importance of the Research Achievements |
資源分野で用いられる衛星画像は地球のほぼ全域をカバーしているが，画像の観測波長数は少なく，鉱物や地質の識別精度は低いのに加えて，地表の詳細がわかるほど空間分解能が高くはない。これらが詳細にわかる多波長数のHP画像や高解像度画像が利用できるのはごく狭い範囲に限られ，コストが高い。これらの問題に対し，本研究では一般のMS衛星画像を撮影範囲全体にわたって，HP画像に変換できる手法，および地質リモートセンシング分野で現在の最高水準の空間分解能まで画像を鮮明化できる手法の2つを開発できた。開発手法はリモートセンシングによる金属・地熱資源探査と地質環境監視の精度の向上に貢献できるので，社会的な意義も高い。
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