Simulation of LiDAR, unmanned ground vehicles, and neural networks for leaf area estimation in orchards

H. Murcia Moreno; S. Lacroix

Jump to Content

Simulation of LiDAR, unmanned ground vehicles, and neural networks for leaf area estimation in orchards

In: Precision agriculture '25

Authors:

H. Murcia Moreno

H. Murcia Moreno

hfmurciamo@laas.fr

Search for other papers by H. Murcia Moreno in
Current site
Google Scholar
PubMed

and

S. Lacroix

S. Lacroix

Search for other papers by S. Lacroix in
Current site
Google Scholar
PubMed

Type:: Chapter

Pages:: 561–568

DOI:: https://doi.org/10.1163/9789004725232_073

Access via:

Dar Hadith al Hassania

Download PDF

The leaf area index (LAI) is vital for assessing plant photosynthetic activity, crucial for optimising orchard management. This study presents a method to estimate leaf area density (LAD) variations and tree LAI using LiDAR data from unmanned ground vehicles (UGVs). Combining 3D tree reconstruction with neural network-based analysis of LiDAR penetration descriptors, the approach effectively estimates canopy parameters. The method was validated through simulation using diverse 3D canopy models, achieving performance metrics: RMSE=0.2 m²/m³, R²=0.95 for LAD and RMSE=0.17 m²/m², R²=0.84 for LAI. Results confirm the potential of LiDAR-based systems for precise orchard canopy monitoring.

Citation Info

Save
Cite
Email this content

Share link with colleague or librarian

You can email a link to this page to a colleague or librarian:
Email this content
or copy the link directly:

https://brill.edhh.ma/edcollchap-oa/book/9789004725232/BP000073.xml
The link was not copied. Your current browser may not support copying via this button.

Link copied successfully

Collapse
Expand

Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

Metrics

	All Time	Past 365 days	Past 30 Days
Abstract Views	0	0	0
Full Text Views	71	51	1
PDF Views & Downloads	98	67	9

African Studies	Education	Media Studies
American Studies	History	Middle East and Islamic Studies
Ancient Near East and Egypt	Human Rights and Humanitarian Law	Musicology
Art History	International Law	Philosophy
Asian Studies	International Relations	Religious Studies
Biblical Studies	Jewish Studies	Slavic and Eurasian Studies
Biology	Languages and Linguistics	Social Sciences
Book History and Cartography	Life Sciences	Theology and World Christianity
Classical Studies	Literature and Cultural Studies

Subjects

Authors

Open Access

Product Information

Company

Contact

Simulation of LiDAR, unmanned ground vehicles, and neural networks for leaf area estimation in orchards

Citation Info

Share link with colleague or librarian

Precision agriculture '25

Table of Contents

Metrics

Metrics