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The role of data science in environmental digital twins: In praise of the arrows

https://doi.org/10.1002/env.2789
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/env.2549openalex-snapshot
Nonparametric statistical downscaling for the fusion of data of different spatiotemporal support
inferredcites →https://doi.org/10.1007/978-3-319-70766-2_6openalex-snapshot
Invalidation of Models and Fitness-for-Purpose: A Rejectionist Approach
inferredcites →https://doi.org/10.1016/j.envsoft.2019.104521openalex-snapshot
Models of everywhere revisited: A technological perspective
inferredcites →https://doi.org/10.1016/j.patter.2021.100359openalex-snapshot
Digital twins of the natural environment
inferredcites →https://doi.org/10.1016/j.spasta.2017.11.006openalex-snapshot
Generalized spatial fusion model framework for joint analysis of point and areal data
inferredcites →https://doi.org/10.1016/j.tree.2019.08.006openalex-snapshot
Data Integration for Large-Scale Models of Species Distributions
inferredcites →https://doi.org/10.1109/mc.2003.1160055openalex-snapshot
The vision of autonomic computing
inferredcites →https://doi.org/10.1109/mc.2004.48openalex-snapshot
Composing adaptive software
inferredcites →https://doi.org/10.3389/fenvs.2019.00121openalex-snapshot
Data Science of the Natural Environment: A Research Roadmap
inferredcites →https://doi.org/10.5194/hess-11-460-2007openalex-snapshot
Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/env.2788openalex-snapshot
Environmental data science: Part 2
inferred← citeshttps://doi.org/10.1007/s10661-025-13923-9openalex-snapshot
Digital twin comprehensive models: a study of ancient tree ecological environment quality assessment based on a cyber-physical system
inferred← citeshttps://doi.org/10.1007/s10980-025-02060-wopenalex-snapshot
Nutrientscape ecology: a whole-system framework to support the understanding and management of coastal nutrient connectivity
inferred← citeshttps://doi.org/10.1016/j.atech.2025.101412openalex-snapshot
Interoperable agricultural digital twins with reinforcement learning intelligence
inferred← citeshttps://doi.org/10.1016/j.envsoft.2025.106431openalex-snapshot
On the future of hydroecological models of everywhere
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2024.131929openalex-snapshot
Developing an open-source flood forecasting system adapted to data-scarce regions: A digital twin coupled with hydrologic-hydrodynamic simulations
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2024.176589openalex-snapshot
Quantifying the relative importance of agricultural land use as a predictor of catchment nitrogen and phosphorus concentrations
inferred← citeshttps://doi.org/10.1029/2024wr039668openalex-snapshot
Uncertainty Quantification for Multi‐Input Fluvial Flood Inundation Using GPR‐ and PCE‐Based Surrogates
inferred← citeshttps://doi.org/10.1080/27525783.2025.2610851openalex-snapshot
Advances, challenges and prospective research when geographical information science meets digital twin
inferred← citeshttps://doi.org/10.1093/af/vfag009openalex-snapshot
Developing a new digital vision for rangeland grazing systems
inferred← citeshttps://doi.org/10.14716/ijtech.v14i8.6840openalex-snapshot
Neural Simulation of Digital Twin of Top Management Motivation Mechanism in Regional Government Agencies
inferred← citeshttps://doi.org/10.3390/w17182731openalex-snapshot
Application of PINNs to Define Roughness Coefficients for Channel Flow Problems
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