Digital Forestry and Smart Technologies: Transforming Forest Monitoring and Assessment
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: 5 March 2027 | Viewed by 70
Editors
Interests: remote sensing; environmental sciences; vegetation; environmental monitoring; agriculture; artificial intelligence; machine learning
Interests: vegetation mapping; vegetation monitoring; land use and land cover; hyperspectral remote sensing; SAR (synthetic aperture radar); geospatial analysis
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; drone-based monitoring; LiDAR; forest inventory; geospatial analysis; big data in forestry
Special Issues, Collections and Topics in MDPI journals
Interests: forest management; large language models; artificial intelligence agents; machine learning; deep learning; scenario forecasting; land use and land cover dynamics
Special Issue Information
Dear Colleagues,
Forest ecosystems play a critical role in supporting biodiversity, regulating climate, and sustaining ecosystem services at local to global scales. However, increasing environmental pressures, including climate change, land-use dynamics, and extreme events, demand more efficient, scalable, and timely approaches for forest monitoring and assessment.
Recent advances in digital technologies have transformed the way forest systems are observed and analyzed. The integration of remote sensing data from satellite, airborne, and unmanned aerial vehicle (UAV) platforms with emerging tools such as artificial intelligence, machine learning, cloud computing, and big data analytics has enabled new possibilities for understanding forest dynamics with unprecedented spatial and temporal detail.
This Special Issue, entitled “Digital Forestry and Smart Technologies: Transforming Forest Monitoring and Assessment”, aims to explore innovative approaches and applications that leverage digital technologies to improve forest monitoring, modeling, and decision-making processes. We welcome contributions that address methodological developments, data integration, and applied studies across different forest types and regions.
Dr. Danielle Elis Garcia Furuya
Dr. Veraldo Liesenberg
Dr. Ana Paula Dalla Corte
Dr. Rudiney Soares Pereira
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- digital forestry
- forest monitoring
- remote sensing
- artificial intelligence
- machine learning
- time-series analysis
- multisensor data integration
- UAV and satellite imagery
- forest management
- climate change
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