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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Bibliographic Details
Main Authors: Hendrik Paasche, Ségolène Dega, Martin Schrön, Peter Dietrich
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Environmental Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2025.1599320/full
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