Google Earth Engineの機械学習とフィールドベースの水文地質学的評価を使用して,乾燥したオアシス環境における砂漠化モニタリング
Adil Moumane1, Youssef Azougarh2,3, Abdelhaq Ait Enajar4
1Department of Geography, Faculty of Humanities and Social Sciences, Ibn Tofail University, Kenitra, 14000, Morocco. adil.moumane@uit.ac.ma.
Scientific reports
|February 21, 2026
まとめ
気候変動と地下水の過剰抽出により,オアシス生態系では砂漠化が加速している. モロッコでのこの研究は,水資源と食料安全保障に影響を及ぼす大規模な土地の劣化を示しています.
科学分野:
- 環境科学 環境科学
- リモートセンシング (リモートセンサー)
- 機械学習 (Machine Learning) とは,機械学習 (Machine Learning) について学ぶことです.
背景:
- オアシスの生態系は,乾燥地域にとって非常に重要ですが,劣化に脆弱です.
- 気候のストレス,土壌の脆弱性,地下水の過剰使用は,オアシスの持続可能性を脅かしています.
研究 の 目的:
- モロッコのテルナタ・オアシスにおける砂漠化の動態を評価する.
- 総合的な分析のために遠隔感知,機械学習,水文地質学,社会経済データを統合する.
主な方法:
- Google Earth Engineで処理されたLandsatアーカイブ (1984-2024) を利用しました.
- 土地の劣化マッピングにグラディエントツリーブースティング (GTB) モデルを適用し,87.2%の精度を達成しました.
- 統合された水文地質学的なフィールドワークと,文脈的なデータを得るための農家のインタビュー.
主要な成果:
- 植物の健康が著しく低下し,砂漠化した土地が広がる.
- 地下水の水位が著しく低下し,水の塩分度が上昇した.
- 農家は,塩分ストレスの増加,高井戸コスト,火災の増加を報告しました.
結論:
- 気候変動の変動と人為的な過剰搾取は,オアシスの砂漠化を加速しています.
- オアシスの劣化と闘うために,統合された水と土地管理戦略が緊急に必要である.
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