Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5267-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5267-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Nov 2024
Data description paper |
| 14 Nov 2024
| 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
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Haitao Yang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Zekun Yang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Qiuli Yang
College of Geography and Remote Sensing Science, Xinjiang University, Ürümqi 800017, China
Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Ürümqi 830017, China
Weiyan Liu
State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, Beijing Forestry University, Beijing 100083, China
Guoran Huang
College of Forestry, Southwest Forestry University, Kunming 650224, China
Yu Ren
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Kai Cheng
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Tianyu Xiang
College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
Mengxi Chen
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Danyang Lin
State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, Beijing Forestry University, Beijing 100083, China
Zhiyong Qi
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Jiachen Xu
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Yixuan Zhang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Guangcai Xu
Beijing GreenValley Technology Co., Ltd., Haidian, Beijing 100091, China
Qinghua Guo
CORRESPONDING AUTHOR
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Institute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Viewed
Total article views: 2,017 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,467 | 398 | 152 | 2,017 | 101 | 38 | 41 |
- HTML: 1,467
- PDF: 398
- XML: 152
- Total: 2,017
- Supplement: 101
- BibTeX: 38
- EndNote: 41
Total article views: 1,074 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Nov 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 908 | 126 | 40 | 1,074 | 54 | 20 | 21 |
- HTML: 908
- PDF: 126
- XML: 40
- Total: 1,074
- Supplement: 54
- BibTeX: 20
- EndNote: 21
Total article views: 943 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 559 | 272 | 112 | 943 | 47 | 18 | 20 |
- HTML: 559
- PDF: 272
- XML: 112
- Total: 943
- Supplement: 47
- BibTeX: 18
- EndNote: 20
Viewed (geographical distribution)
Total article views: 2,017 (including HTML, PDF, and XML)
Thereof 1,974 with geography defined
and 43 with unknown origin.
Total article views: 1,074 (including HTML, PDF, and XML)
Thereof 1,061 with geography defined
and 13 with unknown origin.
Total article views: 943 (including HTML, PDF, and XML)
Thereof 913 with geography defined
and 30 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
5 citations as recorded by crossref.
- Phenological Spatial Divergences Promoted by Climate, Terrain, and Forest Height in a Cold Temperate Forest Landscape: A Case Study of the Greater Khingan Mountain in Hulun Buir, China Y. Tian et al. 10.3390/f16030490
- Study on the Relationship Between 3D Landscape Patterns and Residents’ Comfort in Urban Multi-Unit High-Rise Residential Areas: A Case Study of High-Density Inland City Y. Zhang et al. 10.3390/su17104347
- Performance evaluation and improvement of ICESat-2 and GEDI forest canopy height retrievals in Northeast China C. Yang et al. 10.1080/15481603.2025.2497603
- Determining the Accuracy of Structural Parameters Measured from LiDAR Images in Lowland Oak Forests J. Kolić et al. 10.3390/f16020340
- Enhancing high-resolution forest stand mean height mapping in China through an individual tree-based approach with close-range lidar data Y. Chen et al. 10.5194/essd-16-5267-2024
4 citations as recorded by crossref.
- Phenological Spatial Divergences Promoted by Climate, Terrain, and Forest Height in a Cold Temperate Forest Landscape: A Case Study of the Greater Khingan Mountain in Hulun Buir, China Y. Tian et al. 10.3390/f16030490
- Study on the Relationship Between 3D Landscape Patterns and Residents’ Comfort in Urban Multi-Unit High-Rise Residential Areas: A Case Study of High-Density Inland City Y. Zhang et al. 10.3390/su17104347
- Performance evaluation and improvement of ICESat-2 and GEDI forest canopy height retrievals in Northeast China C. Yang et al. 10.1080/15481603.2025.2497603
- Determining the Accuracy of Structural Parameters Measured from LiDAR Images in Lowland Oak Forests J. Kolić et al. 10.3390/f16020340
Latest update: 16 May 2025
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.
The national-scale continuous maps of arithmetic mean height and weighted mean height across...
Altmetrics
Final-revised paper
Preprint