14:45 〜 15:00
[MGI30-05] HISUIデータを用いた鉱物含有率推定法の精度評価
キーワード：衛星リモートセンシング、ハイパースペクトル画像、熱水変質鉱物、スパーススペクトル分離、Cupriteフィールド（アメリカ合衆国）
Remote sensing using Earth observation satellites has been widely applied to detect signs of metallic deposits and hydrothermally altered minerals, because it can detect them in wide areas. With many observation wavelength ranges (bands) and a large amount of information, Hyperspectral satellite imagery can identify surface materials accurately. HISUI (Hyperspectral Imager SUIte) is one of the recent hyperspectral optical sensors mounted on the “KIBO” of the International Space Station (ISS) for satellite imagery, and the image data have been freely downloadable from 2022. Although more than 277,422 image data are currently available and more detailed analysis is expected, use cases are limited. Therefore, the purpose of this study is to develop a high-precision method of mineral content estimation, which is required for resource exploration, using HISUI images and to demonstrate its usefulness though a case study by selecting the Cuprite field, west Nevada, USA. Because detailed investigations of surface minerals, mostly hydrothermal alteration minerals such as alunite, kaolinite, and opal, have been conducted in the Cuprite field by geological surveys and many remote sensing analyses, this field is most suitable for verifying the accuracy of the proposed method. We used a sparse spectral unmixing method for the content estimation of target minerals and produces a map of mineral distributions using HISUI images taken on 1 October 2021 with a cloud cover of zero. As a result, effectiveness of the combination of the sparse spectral unmixing method and HISUI image data was demonstrated in that we can get a mineral distribution map that corresponds well to the geological map.