土壌深度 0 ～ 20 cm と 20 ～ 50 cm における抽出可能なアルミニウムの予測平均と標準偏差。ピクセル値は、exp(x/10)-1 で元に戻す必要があります。土壌特性の予測は、Innovative Solutions for Decision Agriculture Ltd.（iSDA）によって、機械学習と組み合わせた 30 m ピクセルサイズで行われました。
[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis dataset provides soil property predictions for Africa at 30m pixel size, including extractable aluminum, total carbon, effective cation exchange capacity, and USDA texture class.\u003c/p\u003e\n"],["\u003cp\u003ePredictions are available for two soil depths: 0-20 cm and 20-50 cm, and include predicted mean and standard deviation.\u003c/p\u003e\n"],["\u003cp\u003eData is back-transformed using exp(x/10)-1 for analysis.\u003c/p\u003e\n"],["\u003cp\u003eModel accuracy is lower in dense jungle areas (generally over central Africa), potentially leading to artifacts like banding.\u003c/p\u003e\n"],["\u003cp\u003ePredictions were generated by Innovative Solutions for Decision Agriculture Ltd.(iSDA) using machine learning techniques.\u003c/p\u003e\n"]]],["iSDA provides soil data for Africa at 30m pixel size, focusing on depths of 0-20 cm and 20-50 cm. This includes extractable aluminium, total carbon, effective cation exchange capacity, and USDA texture class. Data includes predicted mean and standard deviation. Pixel values require back-transformation using the formula exp(x/10)-1. Model accuracy may be low in dense jungle areas, potentially showing banding artifacts. Machine learning is employed for soil property predictions.\n"],null,[]]
