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Digital Twins of the Natural Environment

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Digital Twins of the Natural Environment. / Blair, Gordon.
In: Patterns, Vol. 2, No. 10, 100359, 08.10.2021.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Blair, G 2021, 'Digital Twins of the Natural Environment', Patterns, vol. 2, no. 10, 100359. https://doi.org/10.1016/j.patter.2021.100359

APA

Blair, G. (2021). Digital Twins of the Natural Environment. Patterns, 2(10), Article 100359. https://doi.org/10.1016/j.patter.2021.100359

Vancouver

Blair G. Digital Twins of the Natural Environment. Patterns. 2021 Oct 8;2(10):100359. doi: 10.1016/j.patter.2021.100359

Author

Blair, Gordon. / Digital Twins of the Natural Environment. In: Patterns. 2021 ; Vol. 2, No. 10.

Bibtex

@article{a5d5dfa8579049d7b7e1538df322bb4b,
title = "Digital Twins of the Natural Environment",
abstract = "Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment, and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.",
author = "Gordon Blair",
year = "2021",
month = oct,
day = "8",
doi = "10.1016/j.patter.2021.100359",
language = "English",
volume = "2",
journal = "Patterns",
issn = "2666-3899",
publisher = "Cell Press",
number = "10",

}

RIS

TY - JOUR

T1 - Digital Twins of the Natural Environment

AU - Blair, Gordon

PY - 2021/10/8

Y1 - 2021/10/8

N2 - Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment, and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.

AB - Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment, and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.

U2 - 10.1016/j.patter.2021.100359

DO - 10.1016/j.patter.2021.100359

M3 - Journal article

VL - 2

JO - Patterns

JF - Patterns

SN - 2666-3899

IS - 10

M1 - 100359

ER -