Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.6
2.5
Journals
Forests
Special Issues
Modelling and Estimation of Forest Biomass
share announcement

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 158

Special Issue Editors

Dr. Pradip Saud

E-Mail Website
Guest Editor
College of Forestry, Agriculture and Natural Resources, University of Arkansas at Monticello, Monticello, AR 71656, USA
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
Dr. Mukti Ram Subedi

E-Mail Website
Guest Editor
Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA
Interests: remote sensing; biomass and bioenergy; disturbance and restoration ecology; ecological modeling
Prof. Dr. Daniel J. Vega-Nieva

E-Mail Website
Guest Editor
Faculty of Forestry and Environmental Sciences, Juarez University of the State of Durango, Durango 34120, Mexico
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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

29 pages, 28659 KB  
Article
Assessing Anthropogenic Impacts on the Carbon Sink Dynamics in Tropical Lowland Rainforest Using Multiple Remote Sensing Data: A Case Study of Jianfengling, China
by Shijie Mao, Mingjiang Mao, Wenfeng Gong, Yuxin Chen, Yixi Ma, Renhao Chen, Miao Wang, Xiaoxiao Zhang, Jinming Xu, Junting Jia and Lingbing Wu
Forests 2025, 16(10), 1611; https://doi.org/10.3390/f16101611 - 20 Oct 2025
Abstract
Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan [...] Read more.
Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan Tropical Rainforest National Park (NRHTR) from 2015 to 2023. Six machine learning models—Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF)—were evaluated, with RF achieving the highest accuracy (R2 = 0.83). Therefore, RF was employed to generate high-resolution annual AGB maps based on Sentinel-1/2 data fusion, field surveys, socio-economic indicators, and topographic variables. Human pressure was quantified using the Human Influence Index (HII). Threshold analysis revealed a critical breakpoint at ΔHII ≈ 0.1712: below this level, AGB remained relatively stable, whereas beyond it, biomass declined sharply (≈−2.65 mg·ha−1 per 0.01 ΔHII). Partial least squares structural equation modeling (PLS-SEM) identified plantation forests as the dominant negative driver, while GDP (−0.91) and road (−1.04) exerted strong indirect effects through HII, peaking in 2019 before weakening under ecological restoration policies. Spatially, biomass remained resilient within central core zones but declined in peripheral regions associated with road expansion. Temporally, AGB exhibited a trajectory of decline, partial recovery, and renewed loss, resulting in a net reduction of ≈ 0.0393 × 106 mg. These findings underscore the urgent need for a “core stabilization–peripheral containment” strategy integrating disturbance early-warning systems, transportation planning that minimizes impacts on high-AGB corridors, and the strengthening of ecological corridors to maintain carbon-sink capacity and guide differentiated rainforest conservation. Full article
(This article belongs to the Special Issue Modelling and Estimation of Forest Biomass)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop