Modelling and Estimation of Forest Biomass
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: 30 April 2026 | Viewed by 15
Special Issue Editors
Interests: forest growth and yield modeling; survival analysis; taper equation modeling; forest biomass and carbon; stand competition; climate impact; treatment impact on growth and yield
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; biomass and bioenergy; disturbance and restoration ecology; ecological modeling
Interests: forestry and environmental sciences; analysis of information on forest growth; LiDAR; biomass; forest fires; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue invites original research articles dedicated to the modeling and estimation of forest biomass. We also welcome comprehensive review articles that provide a detailed account of the latest methodologies for assessing forest biomass using field inventories, repeated measurements, and advanced remote sensing technologies, such as optical imagery and point clouds (LiDAR, UAV, Sentinel, etc.). Accurate quantification of forest biomass is crucial for estimating carbon sequestration, which plays a significant role in climate change mitigation and engaging landowners and communities in potential carbon credit markets.
Forest biomass estimation can vary significantly according to forest types, tree species, and management objectives, integrating field-based and remote sensing approaches. This will provide valuable guidelines and information to forest managers and practitioners in selecting the appropriate analytical methods. Potential study topics include the following.
- Comparison of empirical and process-based modeling techniques for estimating forest biomass.
- Identifying key factors at the individual tree, stand, and environmental levels that influence allometric relationships in biomass estimation.
- Modeling forest biomasses using machine learning and deep learning approaches.
- Assessing long-term changes in forest biomass dynamics.
- Modeling biomass adjustments following silvicultural treatments.
- Analyzing the impacts of drought, insect pests, and diseases on forest biomass estimation.
- Evaluating changes in forest biomass and structure under environmental stress using remote sensing technologies (e.g., LiDAR and UAV).
- Assessing the effects of wind, hurricanes, and ice damage on tree biomass estimation.
- Investigating how changes in forest structure and composition affect forest biomass estimation.
We encourage authors interested in these topics to discuss their ideas with the Editors prior to submission.
Dr. Pradip Saud
Dr. Mukti Ram Subedi
Prof. Dr. Daniel J. Vega-Nieva
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
- forest biomass
- carbon sequestration
- modeling
- estimation
- remote sensing
- machine learning
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