Comprehensive data aleatory uncertainty propagation in regression random forest using a Monte Carlo approach: a struggle with incomplete data provision using a case study on probabilistic soil moisture regionalization

Data uncertainty never decreases along processing chains and should always be reported alongside processing results. In this study, we attempt to propagate aleatory data uncertainty through a multiple regression analysis to generate regionalized probabilistic soil moisture maps. We employ a non-para...

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التفاصيل البيبلوغرافية

الحاوية / القاعدة:	Frontiers in Environmental Science
المؤلفون الرئيسيون:	Hendrik Paasche, Ségolène Dega, Martin Schrön, Peter Dietrich
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	Frontiers Media S.A. 2025-07-01
الموضوعات:	uncertainty propagation probabilistic prediction Monte Carlo regression random forest soil moisture aleatory uncertainty
الوصول للمادة أونلاين:	https://www.frontiersin.org/articles/10.3389/fenvs.2025.1599320/full