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Abstract

Forest ecosystems play a pivotal role in the global carbon cycle and climate change mitigation. Forest aboveground biomass (AGB), a critical indicator of carbon storage and sequestration capacity, has garnered significant attention in ecological research. Recently, uncrewed aerial vehicle-borne laser scanning (ULS) technology has emerged as a promising tool for rapidly acquiring three-dimensional spatial information on AGB and vegetation carbon storage. This study evaluates the applicability and accuracy of UAV-LiDAR technology in estimating the spatiotemporal dynamics of AGB and vegetation carbon storage in Robinia pseudoacacia (R. pseudoacacia) plantations in the gully regions of the Loess Plateau, China. At the sample plot scale, optimal parameters for individual tree segmentation (ITS) based on the canopy height model (CHM) were determined, and segmentation accuracy was validated. The results showed root mean square error (RMSE) values of 13.17 trees (25.16%) for tree count, 0.40 m (3.57%) for average tree height (AH), and 320.88 kg (16.94%) for AGB. The regression model, which links sample plot AGB with AH and tree count, generated AGB estimates that closely matched the observed AGB values. At the watershed scale, ULS data were used to estimate the AGB and vegetation carbon storage of R. pseudoacacia plantations in the Caijiachuan watershed. The analysis revealed a total of 68,992 trees, with a total carbon storage of 2890.34 Mg and a carbon density of 62.46 Mg ha−1. Low-density forest areas (<1500 trees ha−1) dominated the landscape, accounting for 94.38% of the tree count, 82.62% of the area, and 92.46% of the carbon storage. Analysis of tree-ring data revealed significant variation in the onset of growth decline across different density classes of plantations aged 0–30 years, with higher-density stands exhibiting delayed growth decline compared to lower-density stands. Compared to traditional methods based on diameter at breast height (DBH), carbon storage assessments demonstrated superior accuracy and scientific validity. This study underscores the feasibility and potential of ULS technology for AGB and carbon storage estimation in regions with complex terrain, such as the Loess Plateau. It highlights the importance of accounting for topographic factors to enhance estimation accuracy. The findings provide valuable data support for density management and high-quality development of R. pseudoacacia plantations in the Caijiachuan watershed and present an efficient approach for precise forest carbon sink accounting.

Details

1009240
Title
Estimating Spatiotemporal Dynamics of Carbon Storage in Roinia pseudoacacia Plantations in the Caijiachuan Watershed Using Sample Plots and Uncrewed Aerial Vehicle-Borne Laser Scanning Data
Author
Hu, Yawei 1 ; Sun Ruoxiu 2   VIAFID ORCID Logo  ; He Miaomiao 1 ; Zhao Jiongchang 1 ; Yang, Li 1 ; Huang Shengze 3 ; Zhang, Jianjun 4 

 School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; [email protected] (Y.H.); [email protected] (M.H.); 
 China Agricultural Museum, Beijing 100125, China; [email protected] 
 Asia Air Survey Co., Ltd., Tokyo 160-0023, Japan 
 School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; [email protected] (Y.H.); [email protected] (M.H.);, Jixian National Forest Ecosystem Observation and Research Station, CNERN, School of Soil and Water Conservation, Beijing Forestry University, Linfen 041000, China, Key Laboratory of State Forestry Administration for Soil and Water Conservation, College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China 
Publication title
Volume
17
Issue
8
First page
1365
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
20724292
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-11
Milestone dates
2025-02-16 (Received); 2025-04-09 (Accepted)
Publication history
 
 
   First posting date
11 Apr 2025
ProQuest document ID
3194640352
Document URL
https://www.proquest.com/scholarly-journals/estimating-spatiotemporal-dynamics-carbon-storage/docview/3194640352/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-09-03
Database
ProQuest One Academic