.png){kind=icon}
.png){kind=icon}
Return
Capturing trends in forest structural complexity development using laser scanning techniques
.png){kind=icon}
OA
AI
DOI：10.1016/j.tfp.2025.100954.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Point cloud-derived metrics like gap fraction and Shannon entropy consistently captured forest structural development trends with similar change magnitudes across sensors, remaining robust despite differences in point cloud density and scanning geometry. • Volumetric metrics, such as box-dimension and filled voxel proportion, were highly sensitive to point cloud density, causing inconsistencies across sensors. • The detected changes in Gini height and Gini crown area over a monitoring period of up to nine years were statistically insignificant, highlighting the limitations of these metrics in capturing fine-scale tree-level structural changes, especially with lowdensity point clouds.
Keywords:
Laser scanning
Forest structural complexity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.9
Papers:
297
Citations:
1.5K
Organization
View more organizations