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Volume 17
Issue 24
10.3390/rs17244049
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Article

Quantifying Broad-Leaved Korean Pine Forest Structure Using Terrestrial Laser Scanning (TLS), Changbai Mountain, China

by
Jingcheng Luo
1,2,
Qingda Chen
1,2,
Zhichao Wu
1,2,
Tian Gao
1,
Li Zhou
1,
Jiaojiao Deng
1,
Yansong Zhang
1 and
Dapao Yu
1,*
1
CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(24), 4049; https://doi.org/10.3390/rs17244049
Submission received: 30 October 2025 / Revised: 11 December 2025 / Accepted: 14 December 2025 / Published: 17 December 2025
(This article belongs to the Special Issue Quantitative Remote Sensing for Vegetation Phenology and Regional Landscape Patterns)
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Abstract

Accurate assessment of stand structure is fundamental for elucidating the relationship between forest structure and ecological function, which is vital for enhancing forest quality and ecosystem services. This study, conducted in a 1 hm2 plot of old-growth broadleaved-Korean pine forest in Changbai Mountain, integrated Terrestrial Laser Scanning (TLS), precise geographic coordinates, Quantitative Structure Models (QSM), and wood density data. This methodology enabled a precise, non-destructive quantification of key structural parameters—DBH, tree height, crown overlap, stand volume, and carbon storage—and the development of species-specific allometric equations. The results demonstrated that TLS-derived DBH estimates were 99% accurate, consistent across diameter classes. The overall crown overlap rate (DBH ≥ 5 cm) was 59.1%, decreasing markedly to 26.7% and 19.2% at DBH thresholds of 20 cm and 30 cm, respectively. Allometric models based on DBH showed higher predictive accuracy for stem biomass than for branches, and for broadleaved species over conifers. Notably, conventional models overestimated stem biomass while underestimating branch biomass by 1.34–92.85%, highlighting biases from limited large-tree samples. The integrated TLS-QSM approach provides a robust alternative for accurate biomass estimation, establishing a critical foundation for large-scale, non-destructive allometric modeling. Its broader applicability, however, necessitates further validation across diverse forest ecosystems.
Keywords: Terrestrial Laser Scanning (TLS); QSM model; biomass; model construction Terrestrial Laser Scanning (TLS); QSM model; biomass; model construction

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MDPI and ACS Style

Luo, J.; Chen, Q.; Wu, Z.; Gao, T.; Zhou, L.; Deng, J.; Zhang, Y.; Yu, D. Quantifying Broad-Leaved Korean Pine Forest Structure Using Terrestrial Laser Scanning (TLS), Changbai Mountain, China. Remote Sens. 2025, 17, 4049. https://doi.org/10.3390/rs17244049

AMA Style

Luo J, Chen Q, Wu Z, Gao T, Zhou L, Deng J, Zhang Y, Yu D. Quantifying Broad-Leaved Korean Pine Forest Structure Using Terrestrial Laser Scanning (TLS), Changbai Mountain, China. Remote Sensing. 2025; 17(24):4049. https://doi.org/10.3390/rs17244049

Chicago/Turabian Style

Luo, Jingcheng, Qingda Chen, Zhichao Wu, Tian Gao, Li Zhou, Jiaojiao Deng, Yansong Zhang, and Dapao Yu. 2025. "Quantifying Broad-Leaved Korean Pine Forest Structure Using Terrestrial Laser Scanning (TLS), Changbai Mountain, China" Remote Sensing 17, no. 24: 4049. https://doi.org/10.3390/rs17244049

APA Style

Luo, J., Chen, Q., Wu, Z., Gao, T., Zhou, L., Deng, J., Zhang, Y., & Yu, D. (2025). Quantifying Broad-Leaved Korean Pine Forest Structure Using Terrestrial Laser Scanning (TLS), Changbai Mountain, China. Remote Sensing, 17(24), 4049. https://doi.org/10.3390/rs17244049

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