NCBI PubMed Central
open access
Innovative 3D photosynthetic trait assessment of slash pine using drone-LiDAR fusion and machine learning algorithms.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests#799373
- CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests#797950
- Data-driven interpretability of urban tree species classification from deep learning models and Satellite Image Time Series#161378
- FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data#324921
- A Multi-Sensor Machine Learning Framework Integrating UAV Multispectral Imagery and LiDAR Data for Living Biomass Carbon Stock Estimation in Silviculturally Treated Forests#651903
Record · ID 138448
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive