.png){kind=icon}
.png){kind=icon}
Return
Optimizing canopy cover evaluation: A machine learning approach using LiDAR data
.png){kind=icon}
OA
AI
DOI：10.1016/j.envsoft.2026.106982.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A novel methodology based on IA has been developed to estimate the canopy cover. • The methodology allows flexible training sizes for accurate evaluations. • AI-CanopyMapper is scalable to predict other biophysical variables. • AI-CanopyMapper enables timely forest monitoring.
Keywords:
Machine learning
LiDAR data
Canopy cover
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
E
IF:
4.6
Papers:
235
Citations:
0
Organization
No organization information available