Combating trade in illegal wood and forest products with machine learning

Debanjan Datta; John C. Simeone; Amelia Meadows; Willow Outhwaite; Hin Keong Chen; Nathan Self; Linda Walker; Naren Ramakrishnan

doi:10.1371/journal.pone.0311982

Loading metrics

Open Access

Peer-reviewed

Research Article

Combating trade in illegal wood and forest products with machine learning

Debanjan Datta ,

Contributed equally to this work with: Debanjan Datta, John C. Simeone

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: ddatta@vt.edu

Affiliation Department of Computer Science, Virginia Tech, Arlington, VA, United States of America

https://orcid.org/0000-0001-5997-5142

⨯
John C. Simeone ,

Contributed equally to this work with: Debanjan Datta, John C. Simeone

Roles Data curation, Formal analysis, Resources, Validation, Writing – original draft, Writing – review & editing

Affiliations Simeone Consulting, LLC, Littleton, NH, United States of America, World Wildlife Fund, Washington, DC, United States of America

https://orcid.org/0000-0003-1015-9384

⨯
Amelia Meadows,

Roles Investigation, Project administration

Affiliation World Wildlife Fund, Washington, DC, United States of America
⨯
Willow Outhwaite,

Roles Data curation, Investigation

Affiliation TRAFFIC, Cambridge, United Kingdom
⨯
Hin Keong Chen,

Roles Conceptualization

Affiliation TRAFFIC, Cambridge, United Kingdom
⨯
Nathan Self,

Roles Software, Writing – review & editing

Affiliation Department of Computer Science, Virginia Tech, Arlington, VA, United States of America
⨯
Linda Walker,

Roles Funding acquisition

Affiliation World Wildlife Fund, Washington, DC, United States of America
⨯
Naren Ramakrishnan

Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing

Affiliation Department of Computer Science, Virginia Tech, Arlington, VA, United States of America
⨯

Combating trade in illegal wood and forest products with machine learning

Debanjan Datta,
John C. Simeone,
Amelia Meadows,
Willow Outhwaite,
Hin Keong Chen,
Nathan Self,
Linda Walker,
Naren Ramakrishnan

Published: January 24, 2025
https://doi.org/10.1371/journal.pone.0311982

Reader Comments (0)

Post a new comment on this article

Subject Areas
?

For more information about PLOS Subject Areas, click here.
We want your feedback. Do these Subject Areas make sense for this article? Click the target next to the incorrect Subject Area and let us know. Thanks for your help!

Forests
Is the Subject Area "Forests" applicable to this article?

Thanks for your feedback.
Wood
Is the Subject Area "Wood" applicable to this article?

Thanks for your feedback.
United States
Is the Subject Area "United States" applicable to this article?

Thanks for your feedback.
Machine learning
Is the Subject Area "Machine learning" applicable to this article?

Thanks for your feedback.
Data mining
Is the Subject Area "Data mining" applicable to this article?

Thanks for your feedback.
Machine learning algorithms
Is the Subject Area "Machine learning algorithms" applicable to this article?

Thanks for your feedback.
Timber
Is the Subject Area "Timber" applicable to this article?

Thanks for your feedback.
Network analysis
Is the Subject Area "Network analysis" applicable to this article?

Thanks for your feedback.