Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.4
2.4
Journals
Forests
Special Issues
Forest Inventory: The Monitoring of Biomass and Carbon Stocks
share announcement

Forest Inventory: The Monitoring of Biomass and Carbon Stocks

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: 25 October 2025 | Viewed by 6697

Special Issue Editors

Prof. Dr. Tianxiang Yue

E-Mail
Guest Editor
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Interests: high precision surface modeling method; Chinese population distribution surface modeling method; change detection model; ecological threshold model; scale ecological diversity model; patch connectivity
Special Issues, Collections and Topics in MDPI journals
Dr. Zhe Xu

E-Mail Website
Guest Editor
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: remote sensing; environment modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Zong Wang

E-Mail
Guest Editor
The College of Forestry, Beijing Forestry University, Beijing 100107, China
Interests: forest ecosystems; carbon stock simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forests act as carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in biomass and soil. Therefore, the monitoring biomass and carbon stocks is crucial for our understanding of the capacity of forests to mitigate climate change, our ability to assess the health of forests, and their ability to sustain biodiversity, as well as being crucial in terms of helping governments and international organizations to formulate policies for forest conservation, sustainable land use, and climate change mitigation. This Special Issue aims to explore the critical role of forest inventory in assessing and managing biomass and carbon stocks. Meanwhile, this it also seeks to foster interdisciplinary dialogue and promote advancements in forest inventory methodologies for the effective management of biomass and carbon stocks. Research articles, review papers, and case studies on the following potential topics are all welcome. 

Potential topics include, but are not limited to:

  • Modeling approaches for forest carbon stock estimation;
  • The integration of field and remote sensing data in monitoring biomass and carbon stocks;
  • Predictions of forest carbon stocks and climate change mitigation potential;
  • Methodologies and standards for accounting for forest carbon stocks and changes;
  • Temporal and spatial dynamic variation characteristics and research methods of forest ecosystem carbon storage;
  • Future trends of forest carbon storage under different scenarios;
  • Identification of challenges and gaps in current monitoring and assessment practices.

Prof. Dr. Tianxiang Yue
Dr. Zhe Xu
Dr. Zong Wang
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 inventory
  • biomass assessment
  • carbon stocks
  • monitoring techniques
  • remote sensing
  • data fusion
  • climate change mitigation
  • forest carbon dynamics
  • biodiversity conservation
  • policy implications

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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (6 papers)

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

Research

Jump to: Review

18 pages, 62490 KiB  
Article
Individual Trunk Segmentation and Diameter at Breast Height Estimation Using Mobile LiDAR Scanning
by Angxi Sun, Ruifeng Su, Jinrui Ma and Jianhui Lin
Forests 2025, 16(4), 582; https://doi.org/10.3390/f16040582 - 27 Mar 2025
Viewed by 198
Abstract
Accurate forest monitoring and resource assessment are crucial for sustainable forest management, with tree diameter at breast height (DBH) serving as a key metric for tree growth assessment and carbon storage estimation. In this study, we developed a comprehensive mobile-LiDAR-based point cloud processing [...] Read more.
Accurate forest monitoring and resource assessment are crucial for sustainable forest management, with tree diameter at breast height (DBH) serving as a key metric for tree growth assessment and carbon storage estimation. In this study, we developed a comprehensive mobile-LiDAR-based point cloud processing pipeline to segment individual trees and estimate the DBH of trees. We first conducted terrain extraction using a resolution-passing method combined with a cloth simulation filter. Then, by leveraging the vertical structural characteristics of trees and changes in point cloud density, we achieved high-performance tree trunk segmentation. On this basis, we deployed the Randomized Hough Transform algorithm to estimate the DBH of the trees. Finally, a large-scale experiment was conducted in a forest (Olympic Forest Park, Beijing, China) and we provided experimental results comparing our trunk segmentation and DBH estimation to ground-truth measurements recorded manually. Eventually, our results showed that 97.4% of the trees were accurately segmented, and the DBH estimation error was reduced to 3.2 cm, which shows that the proposed pipeline is able to achieve high-accuracy trunk segmentation and high-precision DBH estimation. Further, this research demonstrates that integrating MLS with SLAM technology can enhance the efficiency and accuracy of forest surveys, providing a valuable tool for future forest management strategies. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

19 pages, 3499 KiB  
Article
Vegetation Mapping and Scenario Simulation in the Poyang Lake Basin of China
by Lingjing Wang, Zemeng Fan, Saibo Li, Yonghui Yao, Zhengping Du and Xuyang Bai
Forests 2025, 16(3), 430; https://doi.org/10.3390/f16030430 - 27 Feb 2025
Viewed by 365
Abstract
Climate change has significantly altered plant habitats within the Earth’s surface system, reshaping the global distribution and succession of vegetation. The spatiotemporal simulation of vegetation dynamics is essential for effective ecosystem management and conservation at regional scales. In this study, an improved method [...] Read more.
Climate change has significantly altered plant habitats within the Earth’s surface system, reshaping the global distribution and succession of vegetation. The spatiotemporal simulation of vegetation dynamics is essential for effective ecosystem management and conservation at regional scales. In this study, an improved method is developed to analyze the vegetation patterns and scenarios in the Poyang Lake basin, based on the High-Accuracy Surface Modeling (HASM) method and the improved Holdridge Life Zone (HLZ) ecosystem model. HASM is applied to generate high-resolution (250 m × 250 m) spatial grid data for key climate parameters, including mean annual biotemperature (MAB), total annual precipitation (TAP), and potential evapotranspiration ratio (PER), for each decade from 1961 to 2050. The distribution thresholds of vegetation types are calculated based on current vegetation data, MAB, TAP, PER, longitude, latitude, and elevation datasets. In the improved HLZ ecosystem model, the classification parameters of vegetation types have been expanded from three to six. The simulation results indicate that cultivated vegetation, subtropical coniferous forest, and subtropical grassland are the dominant vegetation types, accounting for 75.88% of the total area. Between 2020 and 2050, subtropical coniferous forest is projected to experience the greatest decrease in area, shrinking by an average of 2.65 × 103 km2 per decade. In contrast, subtropical evergreen–deciduous broadleaf mixed forest is expected to undergo the largest increase, expanding by an average of 1.96 × 103 km2 per decade. Vegetation types in high-altitude regions exhibit the most rapid changes, with an average decadal variation of 15.26%, whereas low-altitude regions show relatively slower changes, averaging 0.52% per decade. Overall, subtropical grassland, subtropical coniferous forest, and subtropical evergreen–deciduous broadleaf mixed forest in the Poyang Lake basin demonstrate high sensitivity to projected climate change scenarios. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

13 pages, 3574 KiB  
Article
Effects of Forest Land Mulching on the Soil CO2 Emission Rate of Phyllostachys violascens Forests
by Zhan Shen, Dongping Zha, Xinglan Zu, Jianmin Shi, Zuyao Li and Shuangshuang Chu
Forests 2025, 16(1), 106; https://doi.org/10.3390/f16010106 - 9 Jan 2025
Viewed by 530
Abstract
This study investigates the dynamics of soil CO2 emissions during the cover period of Phyllostachys violascens and the impact of different cover measures, aiming to provide references for reducing the environmental effects of bamboo cover. An L27 (913) orthogonal [...] Read more.
This study investigates the dynamics of soil CO2 emissions during the cover period of Phyllostachys violascens and the impact of different cover measures, aiming to provide references for reducing the environmental effects of bamboo cover. An L27 (913) orthogonal experimental design was employed, setting the following variables: (1) heating materials: chicken manure, straw cake, and wheat ash; (2) thickness of husk layer: 15 cm, 25 cm, and 35 cm; (3) soil moisture levels before covering: moisture to 10 cm, 15 cm, and 20 cm. The soil CO2 emission rate showed a unimodal curve, with a significant overall increase during the cover period. Throughout the entire cover period, the average soil CO2 emission rate (25.39 μmol·m−2·s−1) was 5.1 times higher than that of the uncovered Lei bamboo forest (5.02 μmol·m−2·s−1) during the same period. Thicker husk layers (25 cm and 35 cm) corresponded to higher soil CO2 emission rates, with significant differences noted among the thicknesses. When the soil was moist to 10 cm, the CO2 emission rate was highest (62.51 μmol·m−2·s−1); moisture to 15 cm and 20 cm resulted in significantly lower emission rates. Chicken manure produced the highest peak CO2 emissions in the third week, at 70.64 μmol·m−2·s−1, while straw cake and wheat ash reached their peaks in the fifth week, at 66.56 μmol·m−2·s−1 and 57.58 μmol·m−2·s−1, respectively. The interactions between the three factors (heating materials, husk layer thickness, and moisture levels) significantly affected the soil CO2 emission rates. By optimally configuring these factors, CO2 emissions can be regulated. This study recommends using wheat ash or straw cake as heating materials, combined with a 25 cm husk layer thickness, and moistening the soil to 15 cm before covering. This approach effectively reduces the peak and total soil CO2 emissions while ensuring suitable soil temperatures for the growth of bamboo shoots in spring. This research provides a scientific basis for the environmental management of bamboo forests, aiding in the optimization of covering measures to achieve low-carbon and sustainable bamboo management. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

23 pages, 19922 KiB  
Article
Integrating Ward’s Clustering Stratification and Spatially Correlated Poisson Disk Sampling to Enhance the Accuracy of Forest Aboveground Carbon Stock Estimation
by Mingrui Xu, Xuelian Han, Jialong Zhang, Kai Huang, Min Peng, Bo Qiu and Kun Yang
Forests 2024, 15(12), 2111; https://doi.org/10.3390/f15122111 - 28 Nov 2024
Viewed by 658
Abstract
In forest resource surveys, using sampling methods to estimate aboveground carbon stock (ACS) can significantly reduce survey costs. This study improves the accuracy of ACS estimation by optimizing the stratified sampling design. The sampling process was divided into two stages: stratification and intra-stratum [...] Read more.
In forest resource surveys, using sampling methods to estimate aboveground carbon stock (ACS) can significantly reduce survey costs. This study improves the accuracy of ACS estimation by optimizing the stratified sampling design. The sampling process was divided into two stages: stratification and intra-stratum sampling. For stratification, remote sensing features were used as stratification variables, and a spatial clustering stratification method was introduced. For intra-stratum sampling, a composite method, Spatially Correlated Poisson Disk Sampling (SCPDS), was proposed. Using Random Forest (RF) and the sample points selected by SCPDS, the ACS was estimated and compared with traditional sampling methods for Pinus densata in Shangri-La, Yunnan, China. The results showed that (1) by selecting effective stratification variables (e.g., texture features), the required sample size was reduced by up to 19.35% compared to that of simple random sampling; (2) the Ward clustering method greatly improved stratification heterogeneity; (3) for intra-stratum sampling, the SCPDS method ensured spatial independence within strata, particularly at low sampling rates (1%–5%), where its error was significantly lower than that of other methods, indicating greater stability and improved accuracy; (4) the SCPDS-based model achieved the best fitting accuracy, with R2 = 0.886. The total carbon stock of Pinus densata using RF was 7,872,787.5 t, closely matching forest management inventory (FMI) data. Through sampling, even with a relatively small sample size, the representative plots can still accurately reflect ACS estimates that are consistent with those derived from large-scale plot surveys. Thus, the optimized stratified sampling method effectively reduced sampling costs while significantly enhancing the stability and accuracy of the results. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

19 pages, 27172 KiB  
Article
Quantitative Evaluation of the Applicability of Classical Forest Ecosystem Carbon Cycle Models in China: A Case Study of the Biome-BGC Model
by Minzhe Fang, Wei Liu, Jieyu Zhang, Jun Ma, Zhisheng Liang and Qiang Yu
Forests 2024, 15(9), 1609; https://doi.org/10.3390/f15091609 - 12 Sep 2024
Cited by 1 | Viewed by 1284
Abstract
The Biome-BGC model is a classic forest ecosystem carbon cycle model driven by remote sensing and plant trait data, and it has been widely applied in various regions of China over the years. However, does the Biome-BGC model have good applicability in all [...] Read more.
The Biome-BGC model is a classic forest ecosystem carbon cycle model driven by remote sensing and plant trait data, and it has been widely applied in various regions of China over the years. However, does the Biome-BGC model have good applicability in all regions of China? This question implies that the rationality of some applications of the Biome-BGC model in China might be questionable. To quantitatively assess the overall spatial applicability of the Biome-BGC model in China’s vegetation ecosystems, this study selected ten representative forest and grassland ecosystem sites, all of which have publicly available carbon flux data. In this study, we first used the EFAST method to identify the sensitive ecophysiological parameters of the Biome-BGC model at these sites. Subsequently, we calibrated the optimal values of these sensitive parameters through a literature review and the PEST method and then used these to drive the Biome-BGC model to simulate the productivity (including GPP and NEP) of these ten forest and grassland ecosystems in China. Finally, we compared the simulation accuracy of the Biome-BGC model at these ten sites in detail and established the spatial pattern of the model’s applicability across China. The results show that the sensitive ecophysiological parameters of the Biome-BGC model vary with spatial distribution, plant functional types, and model output variables. After conducting parameter sensitivity analysis and optimization, the simulation accuracy of the Biome-BGC model can be significantly improved. Additionally, for forest ecosystems in China, the model’s simulation accuracy decreases from north to south, while for grassland ecosystems, the accuracy increases from north to south. This study provides a set of localized ecophysiological parameters and advocates that the use of the Biome-BGC model should be based on parameter sensitivity analysis and optimization. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

Review

Jump to: Research

22 pages, 7710 KiB  
Review
Review of the Current Status and Development Trend of Global Forest Carbon Storage Research Based on Bibliometrics
by Chenchen Wu, Yang Yang and Tianxiang Yue
Forests 2024, 15(9), 1498; https://doi.org/10.3390/f15091498 - 27 Aug 2024
Viewed by 2815
Abstract
Forests are one of the largest terrestrial ecosystems on Earth, absorbing carbon dioxide from the atmosphere through photosynthesis and storing it as organic carbon, thereby mitigating global warming. Conducting bibliometric analysis of forest carbon storage can identify current research trends and hot issues [...] Read more.
Forests are one of the largest terrestrial ecosystems on Earth, absorbing carbon dioxide from the atmosphere through photosynthesis and storing it as organic carbon, thereby mitigating global warming. Conducting bibliometric analysis of forest carbon storage can identify current research trends and hot issues in this field, providing data support for researchers and policy makers. This review article provides a comprehensive bibliometric analysis of global forest carbon storage research, using databases from the Web of Science Core Collection. CiteSpace software (6.2.6 version) was employed to visualize and analyze the data, focusing on key researchers, institutions, and countries, as well as major research themes and emerging trends. The main findings are as follows: (1) Since the 21st century, the publication volume in this field has been increasing, with the United States and China being the top contributors. (2) There is active collaboration among key authors, institutions, and countries, with a notable close-knit network centered around French author Philippe Ciais. This group includes nearly half of the field’s authors and many of them are crucial for advancing research in this field. (3) Cluster and citation burst analyses suggest that future research will focus more on the impact of forest management policies on carbon stocks, with particular attention to the roles of northern temperate forests and mangroves in global carbon storage. These findings provide valuable insights into the current state and future directions of forest carbon storage research. This article is instrumental in elucidating the role of forest ecosystems within the global carbon cycle, evaluating the impacts of anthropogenic activities on forest carbon stocks, and informing the development of effective climate change mitigation strategies. Full article
(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop