Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5267-2024
https://doi.org/10.5194/essd-16-5267-2024
Data description paper
 | 
14 Nov 2024
Data description paper |  | 14 Nov 2024

Enhancing high-resolution forest stand mean height mapping in China through an individual tree-based approach with close-range lidar data

Yuling Chen, Haitao Yang, Zekun Yang, Qiuli Yang, Weiyan Liu, Guoran Huang, Yu Ren, Kai Cheng, Tianyu Xiang, Mengxi Chen, Danyang Lin, Zhiyong Qi, Jiachen Xu, Yixuan Zhang, Guangcai Xu, and Qinghua Guo

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Latest update: 08 Mar 2025
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Short summary
The national-scale continuous maps of arithmetic mean height and weighted mean height across China address the challenges of accurately estimating forest stand mean height using a tree-based approach. These maps produced in this study provide critical datasets for forest sustainable management in China, including climate change mitigation (e.g., terrestrial carbon estimation), forest ecosystem assessment, and forest inventory practices.
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