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クラウドの除去とデータ再構築のためのSentinel-2のギャップ埋めるテクニックの評価

Said Grich1, Jamal Elfarkh2, Nadia Ouaadi2

  • 1Center for Remote Sensing Applications (CRSA), University Mohammed VI Polytechnic (UM6P), Benguerir, 43150, Morocco. said.grich@um6p.ma.

Scientific reports
|February 17, 2026
PubMed
まとめ

この研究では,Sentinel-2の衛星画像の空白を埋める方法を評価しています. 空間時間的な方法,特にクラスタリングと線形回帰 (CLR) は,さまざまなシナリオで信頼性の高いデータ復元のための最高のパフォーマンスを示しました.

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