Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision

Feng Luo; Ling Liu; G. Geoff Wang; Vijay Kumar; Mark S. Ashton; Jacob Abernethy; Fatemeh Afghah; Matthew H.E.M. Browning; David Coyle; Philip Dames; Tom O'Halloran; James Hays; Patrick Heisl; Chenfanfu Jiang; Puskar Khanal; Venkat Narayan Krovi; Sara Kuebbing; Nianyi Li; Jing Jing Liang; Ninghao Liu; Steve McNulty; Christopher M. Oswalt; Neil Pederson; Demetri Terzopoulos; Christopher W. Woodall; Yongkai Wu; Jian Yang; Yin Yang; Liang Zhao

doi:10.1109/CogMI58952.2023.00011

Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision

Feng Luo, Ling Liu, G. Geoff Wang, Vijay Kumar, Mark S. Ashton, Jacob Abernethy, Fatemeh Afghah, Matthew H.E.M. Browning, David Coyle, Philip Dames, Tom O'Halloran, James Hays, Patrick Heisl, Chenfanfu Jiang, Puskar Khanal, Venkat Narayan Krovi, Sara Kuebbing, Nianyi Li, Jing Jing Liang, Ninghao LiuSteve McNulty, Christopher M. Oswalt, Neil Pederson, Demetri Terzopoulos, Christopher W. Woodall, Yongkai Wu, Jian Yang, Yin Yang, Liang Zhao

Forestry and Natural Resources

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Forests and forest ecosystems are vital to our social, economic, and environmental well-being. However, climate change and climate-driven disturbances (CDDs) are undermining the health and resilience of forests worldwide and pose significant uncertainty to sustainable forest management. Climate-smart forestry (CSF) remains a grand challenge in practice due to our limited knowledge of how forests respond to climate change and our abilities to collect related information to empower decision making. Rapid advances in artificial intelligence (AI) can offer a timely opportunity to address the challenges in CSF. We argue that the AI-enabled, next-generation CSF can be achievable through synergistically coordinated and transdisciplinary efforts that develop and advance foundational and use-inspired AI technologies that can lead to building next-generation forest decision support systems.

Original language	English
Title of host publication	Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023
Pages	1-10
Number of pages	10
ISBN (Electronic)	9798350323832
DOIs	https://doi.org/10.1109/CogMI58952.2023.00011
State	Published - 2023
Event	5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023 - Atlanta, United States Duration: Nov 1 2023 → Nov 3 2023

Publication series

Name	Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023

Conference

Conference	5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023
Country/Territory	United States
City	Atlanta
Period	11/1/23 → 11/3/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

artificial intelligence
climate-smart forestry

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems and Management
Statistics, Probability and Uncertainty
Modeling and Simulation
Cognitive Neuroscience

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CogMI58952.2023.00011

Cite this

Luo, F., Liu, L., Wang, G. G., Kumar, V., Ashton, M. S., Abernethy, J., Afghah, F., Browning, M. H. E. M., Coyle, D., Dames, P., O'Halloran, T., Hays, J., Heisl, P., Jiang, C., Khanal, P., Krovi, V. N., Kuebbing, S., Li, N., Liang, J. J., ... Zhao, L. (2023). Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. In Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023 (pp. 1-10). (Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023). https://doi.org/10.1109/CogMI58952.2023.00011

@inproceedings{e742be5e32a147ab8c0292565ebdeb9f,

title = "Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision",

abstract = "Forests and forest ecosystems are vital to our social, economic, and environmental well-being. However, climate change and climate-driven disturbances (CDDs) are undermining the health and resilience of forests worldwide and pose significant uncertainty to sustainable forest management. Climate-smart forestry (CSF) remains a grand challenge in practice due to our limited knowledge of how forests respond to climate change and our abilities to collect related information to empower decision making. Rapid advances in artificial intelligence (AI) can offer a timely opportunity to address the challenges in CSF. We argue that the AI-enabled, next-generation CSF can be achievable through synergistically coordinated and transdisciplinary efforts that develop and advance foundational and use-inspired AI technologies that can lead to building next-generation forest decision support systems.",

keywords = "artificial intelligence, climate-smart forestry",

author = "Feng Luo and Ling Liu and Wang, {G. Geoff} and Vijay Kumar and Ashton, {Mark S.} and Jacob Abernethy and Fatemeh Afghah and Browning, {Matthew H.E.M.} and David Coyle and Philip Dames and Tom O'Halloran and James Hays and Patrick Heisl and Chenfanfu Jiang and Puskar Khanal and Krovi, {Venkat Narayan} and Sara Kuebbing and Nianyi Li and Liang, {Jing Jing} and Ninghao Liu and Steve McNulty and Oswalt, {Christopher M.} and Neil Pederson and Demetri Terzopoulos and Woodall, {Christopher W.} and Yongkai Wu and Jian Yang and Yin Yang and Liang Zhao",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023 ; Conference date: 01-11-2023 Through 03-11-2023",

year = "2023",

doi = "10.1109/CogMI58952.2023.00011",

language = "English",

series = "Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023",

pages = "1--10",

booktitle = "Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023",

}

Luo, F, Liu, L, Wang, GG, Kumar, V, Ashton, MS, Abernethy, J, Afghah, F, Browning, MHEM, Coyle, D, Dames, P, O'Halloran, T, Hays, J, Heisl, P, Jiang, C, Khanal, P, Krovi, VN, Kuebbing, S, Li, N, Liang, JJ, Liu, N, McNulty, S, Oswalt, CM, Pederson, N, Terzopoulos, D, Woodall, CW, Wu, Y, Yang, J, Yang, Y & Zhao, L 2023, Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. in Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023. Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023, pp. 1-10, 5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023, Atlanta, United States, 11/1/23. https://doi.org/10.1109/CogMI58952.2023.00011

Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. / Luo, Feng; Liu, Ling; Wang, G. Geoff et al.
Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023. 2023. p. 1-10 (Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Artificial Intelligence for Climate Smart Forestry

T2 - 5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023

AU - Luo, Feng

AU - Liu, Ling

AU - Wang, G. Geoff

AU - Kumar, Vijay

AU - Ashton, Mark S.

AU - Abernethy, Jacob

AU - Afghah, Fatemeh

AU - Browning, Matthew H.E.M.

AU - Coyle, David

AU - Dames, Philip

AU - O'Halloran, Tom

AU - Hays, James

AU - Heisl, Patrick

AU - Jiang, Chenfanfu

AU - Khanal, Puskar

AU - Krovi, Venkat Narayan

AU - Kuebbing, Sara

AU - Li, Nianyi

AU - Liang, Jing Jing

AU - Liu, Ninghao

AU - McNulty, Steve

AU - Oswalt, Christopher M.

AU - Pederson, Neil

AU - Terzopoulos, Demetri

AU - Woodall, Christopher W.

AU - Wu, Yongkai

AU - Yang, Jian

AU - Yang, Yin

AU - Zhao, Liang

PY - 2023

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N2 - Forests and forest ecosystems are vital to our social, economic, and environmental well-being. However, climate change and climate-driven disturbances (CDDs) are undermining the health and resilience of forests worldwide and pose significant uncertainty to sustainable forest management. Climate-smart forestry (CSF) remains a grand challenge in practice due to our limited knowledge of how forests respond to climate change and our abilities to collect related information to empower decision making. Rapid advances in artificial intelligence (AI) can offer a timely opportunity to address the challenges in CSF. We argue that the AI-enabled, next-generation CSF can be achievable through synergistically coordinated and transdisciplinary efforts that develop and advance foundational and use-inspired AI technologies that can lead to building next-generation forest decision support systems.

AB - Forests and forest ecosystems are vital to our social, economic, and environmental well-being. However, climate change and climate-driven disturbances (CDDs) are undermining the health and resilience of forests worldwide and pose significant uncertainty to sustainable forest management. Climate-smart forestry (CSF) remains a grand challenge in practice due to our limited knowledge of how forests respond to climate change and our abilities to collect related information to empower decision making. Rapid advances in artificial intelligence (AI) can offer a timely opportunity to address the challenges in CSF. We argue that the AI-enabled, next-generation CSF can be achievable through synergistically coordinated and transdisciplinary efforts that develop and advance foundational and use-inspired AI technologies that can lead to building next-generation forest decision support systems.

KW - artificial intelligence

KW - climate-smart forestry

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DO - 10.1109/CogMI58952.2023.00011

M3 - Conference contribution

AN - SCOPUS:85186492596

T3 - Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023

SP - 1

EP - 10

BT - Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023

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ER -

Luo F, Liu L, Wang GG, Kumar V, Ashton MS, Abernethy J et al. Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. In Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023. 2023. p. 1-10. (Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023). doi: 10.1109/CogMI58952.2023.00011

Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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