Application and Development of Artificial Intelligence Technology in Forestry Management
A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".
Deadline for manuscript submissions: 15 December 2025 | Viewed by 110
Special Issue Editors
Interests: intelligent processing of agricultural and forestry products
Interests: forestry engineering
Special Issue Information
Dear Colleagues,
Research into forestry operations is pivotal to global ecological security and sustainable development. Forests, covering 31% of Earth's land area, sustain 80% of terrestrial biodiversity and support the livelihoods of over 1.6 billion people. However, climate change, wildfires, and pests contribute to an annual loss of 10 million hectares of forests, exacerbating biodiversity collapse and carbon sink degradation. Optimizing forest operations through technology-driven strategies has therefore become critical. Developing scalable solutions that balance economic viability with ecological preservation requires urgent interdisciplinary research into AI-enhanced monitoring, precision harvesting, and adaptive management frameworks.
This Special Issue, “Application and Development of Artificial Intelligence Technology in Forestry Operations”, aims to explore cutting-edge advancements in AI-driven solutions for sustainable forest management. By integrating technologies such as machine learning, the IoT, and remote sensing, AI is revolutionizing forest management. This Special Issue seeks to compile innovative research on AI applications in forestry, addressing challenges such as forest resource monitoring and management, forest cultivation and management, forest protection, disaster prevention, and wildlife conservation.
This Special Issue prioritizes research studies addressing the AI–forestry nexus, particularly those that bridge the gap between algorithmic innovation and field implementation. By fostering convergence across ecological science, data engineering, and policy design, we aim to establish AI as indispensable to next-generation sustainable forest management.
Dr. Weijun Xie
Dr. Ying Liu
Dr. Deyong Yang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- precision breeding
- phenotypic analysis
- forest mapping
- wildfire monitoring
- pest management
- autonomous harvesting systems
- defect detection
- wildlife conservation
- forest food resource management
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