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

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Wydane w:Remote Sensing vol. 17, no. 8 (2025), p. 1365
1. autor: Hu, Yawei
Kolejni autorzy: Sun Ruoxiu, He Miaomiao, Zhao Jiongchang, Yang, Li, Huang Shengze, Zhang, Jianjun
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MDPI AG
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022 |a 2072-4292 
024 7 |a 10.3390/rs17081365  |2 doi 
035 |a 3194640352 
045 2 |b d20250101  |b d20251231 
084 |a 231556  |2 nlm 
100 1 |a Hu, Yawei  |u School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; huyawei@bjfu.edu.cn (Y.H.); hmm3230681@bjfu.edu.cn (M.H.); 
245 1 |a Estimating Spatiotemporal Dynamics of Carbon Storage in <i>Roinia pseudoacacia</i> Plantations in the Caijiachuan Watershed Using Sample Plots and Uncrewed Aerial Vehicle-Borne Laser Scanning Data 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Carbon cycle 
653 |a Height 
653 |a Gullies 
653 |a Forestry 
653 |a Scanners 
653 |a Scientific validity 
653 |a Laser applications 
653 |a Segmentation 
653 |a Vegetation 
653 |a Watersheds 
653 |a Lidar 
653 |a Feasibility studies 
653 |a Trees 
653 |a Density 
653 |a Forests 
653 |a Climate change 
653 |a Dendrochronology 
653 |a Water conservation 
653 |a Remote sensing 
653 |a Spatial data 
653 |a Forest ecosystems 
653 |a Lasers 
653 |a Root-mean-square errors 
653 |a Terrestrial ecosystems 
653 |a Climate change mitigation 
653 |a Methods 
653 |a Plantations 
653 |a Parameter estimation 
653 |a Accuracy 
653 |a Regression models 
653 |a Biomass 
653 |a Plateaus 
653 |a Carbon sequestration 
653 |a Forest biomass 
653 |a Ecological research 
653 |a Data collection 
653 |a Tree rings 
653 |a Carbon sinks 
653 |a Morphology 
653 |a Estimation 
700 1 |a Sun Ruoxiu  |u China Agricultural Museum, Beijing 100125, China; sunruoxiu0331@126.com 
700 1 |a He Miaomiao  |u School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; huyawei@bjfu.edu.cn (Y.H.); hmm3230681@bjfu.edu.cn (M.H.); 
700 1 |a Zhao Jiongchang  |u School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; huyawei@bjfu.edu.cn (Y.H.); hmm3230681@bjfu.edu.cn (M.H.); 
700 1 |a Yang, Li  |u School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; huyawei@bjfu.edu.cn (Y.H.); hmm3230681@bjfu.edu.cn (M.H.); 
700 1 |a Huang Shengze  |u Asia Air Survey Co., Ltd., Tokyo 160-0023, Japan 
700 1 |a Zhang, Jianjun  |u School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; huyawei@bjfu.edu.cn (Y.H.); hmm3230681@bjfu.edu.cn (M.H.); 
773 0 |t Remote Sensing  |g vol. 17, no. 8 (2025), p. 1365 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3194640352/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3194640352/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3194640352/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch