LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure
Accurate and efficient estimation of individual tree aboveground biomass (AGB) is crucial for precision forestry and forest carbon stock assessment. While the influence of spatial structure on biomass is acknowledged, its integration into individual tree AGB models for enhancing accuracy remains equ...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24014304 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846121335315496960 |
|---|---|
| author | Zhi Liu Xiaoli Zhang Yong Wu Yuansu Xu Zhengying Cao Zhibo Yu Zihang Feng Hongbin Luo Chi Lu Weibin Wang Guanglong Ou |
| author_facet | Zhi Liu Xiaoli Zhang Yong Wu Yuansu Xu Zhengying Cao Zhibo Yu Zihang Feng Hongbin Luo Chi Lu Weibin Wang Guanglong Ou |
| author_sort | Zhi Liu |
| collection | DOAJ |
| description | Accurate and efficient estimation of individual tree aboveground biomass (AGB) is crucial for precision forestry and forest carbon stock assessment. While the influence of spatial structure on biomass is acknowledged, its integration into individual tree AGB models for enhancing accuracy remains equivocal. The UAV-LiDAR data and individual tree AGB destructively measured of natural Pinus kesiya var. langbianensis were collected from 2022 to 2023. First, Individual tree attributes and spatial structures were extracted and evaluated from LiDAR data. Then, two AGB models were developed and compared: one independent of diameter at breast height (DBH) and another incorporating stand spatial structure parameters, including the uniform angle index (W), neighborhood comparison (U), stand level rate (Si), and competition index (UCi). The results showed that AGB models can be effectively constructed based on canopy features alone, even without the inclusion of DBH. The accuracy of individual tree AGB models was improved when spatial structure parameters were incorporated. In particular, the introduction of angular scales improved the accuracy of the AGB model most significantly. On average, R2 increased by 8.668%, while RMSE, SEE, and TRE decreased by 11.262%, 10.619%, and 7.570%, respectively. Spatial structure parameters facilitated a more precise and realistic depiction of competitive interactions and spatial distribution patterns among trees, thereby enhancing model performance. It demonstrated an effective approach for leveraging UAV-LiDAR data to rapidly and precisely estimate AGB and carbon stocks for individual trees, forest stands and regional scales. |
| format | Article |
| id | doaj-art-91171018fd444ad7afb5f94d5850d6e5 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-91171018fd444ad7afb5f94d5850d6e52024-12-16T05:35:44ZengElsevierEcological Indicators1470-160X2024-12-01169112973LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structureZhi Liu0Xiaoli Zhang1Yong Wu2Yuansu Xu3Zhengying Cao4Zhibo Yu5Zihang Feng6Hongbin Luo7Chi Lu8Weibin Wang9Guanglong Ou10Key Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, ChinaKey Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, China; Corresponding authors.Key Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650233, China; Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming 650233, China; Corresponding authors.Accurate and efficient estimation of individual tree aboveground biomass (AGB) is crucial for precision forestry and forest carbon stock assessment. While the influence of spatial structure on biomass is acknowledged, its integration into individual tree AGB models for enhancing accuracy remains equivocal. The UAV-LiDAR data and individual tree AGB destructively measured of natural Pinus kesiya var. langbianensis were collected from 2022 to 2023. First, Individual tree attributes and spatial structures were extracted and evaluated from LiDAR data. Then, two AGB models were developed and compared: one independent of diameter at breast height (DBH) and another incorporating stand spatial structure parameters, including the uniform angle index (W), neighborhood comparison (U), stand level rate (Si), and competition index (UCi). The results showed that AGB models can be effectively constructed based on canopy features alone, even without the inclusion of DBH. The accuracy of individual tree AGB models was improved when spatial structure parameters were incorporated. In particular, the introduction of angular scales improved the accuracy of the AGB model most significantly. On average, R2 increased by 8.668%, while RMSE, SEE, and TRE decreased by 11.262%, 10.619%, and 7.570%, respectively. Spatial structure parameters facilitated a more precise and realistic depiction of competitive interactions and spatial distribution patterns among trees, thereby enhancing model performance. It demonstrated an effective approach for leveraging UAV-LiDAR data to rapidly and precisely estimate AGB and carbon stocks for individual trees, forest stands and regional scales.http://www.sciencedirect.com/science/article/pii/S1470160X24014304Pinus kesiya var. langbianensisIndividual tree AGB modelUAV-LiDARSpatial structureDummy variable |
| spellingShingle | Zhi Liu Xiaoli Zhang Yong Wu Yuansu Xu Zhengying Cao Zhibo Yu Zihang Feng Hongbin Luo Chi Lu Weibin Wang Guanglong Ou LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure Ecological Indicators Pinus kesiya var. langbianensis Individual tree AGB model UAV-LiDAR Spatial structure Dummy variable |
| title | LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure |
| title_full | LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure |
| title_fullStr | LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure |
| title_full_unstemmed | LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure |
| title_short | LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure |
| title_sort | lidar based individual tree agb modeling of pinus kesiya var langbianensis by incorporating spatial structure |
| topic | Pinus kesiya var. langbianensis Individual tree AGB model UAV-LiDAR Spatial structure Dummy variable |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24014304 |
| work_keys_str_mv | AT zhiliu lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT xiaolizhang lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT yongwu lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT yuansuxu lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT zhengyingcao lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT zhiboyu lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT zihangfeng lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT hongbinluo lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT chilu lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT weibinwang lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure AT guanglongou lidarbasedindividualtreeagbmodelingofpinuskesiyavarlangbianensisbyincorporatingspatialstructure |