Developing a generalized nonlinear mixed-effects biomass model at stand-level under different age conditions for Chinese fir based on LiDAR and ground survey data in southern China
This study highlights the effectiveness of airborne LiDAR data in providing efficient and precise estimates of stand biomass. It also emphasizes the significant role of stand developmental stages in biomass modeling. The findings contribute to the development of a rigorous and scalable framework for large-scale artificial forest biomass estimation, which has important implications for forest resource monitoring, ecological industry development, and ecosystem management strategies.
Authors
- Jinsheng Ye
- Ram P. Sharma (ORCID: https://orcid.org/0000-0002-8623-6211)
- Qiulai Wang (ORCID: https://orcid.org/0000-0002-8691-9012)
- Liyong Fu (ORCID: https://orcid.org/0000-0002-5794-9458)
- Yongfeng Yang (ORCID: https://orcid.org/0000-0003-0402-4440)
- Ziyang Liu (ORCID: https://orcid.org/0000-0003-1984-7378)
- Lang Bai (ORCID: https://orcid.org/0000-0001-5042-4336)
- Tian‐Bao Huang
- Xinsheng Zhu
Institutions
- Tribhuvan University (NP)
- Institute of Forest Resource Information Techniques (CN)
- Chinese Academy of Forestry (CN)
- State Forestry and Grassland Administration (CN)
- Jiangxi Province Forestry Survey Planning Institute (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-05-08
- DOI
- https://doi.org/10.3389/fpls.2025.1532138
- Citations
- 4
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.20