2D LiDAR-Based Eucalyptus Tree Measurement and Monitoring System using Mobile Application
LiDAR technology has rapidly advanced, offering highly accurate solutions for tree geometry estimation, which is particularly valuable in agriculture and forestry. Its ability to capture precise 2D and 3D data has revolutionized tree detection and measurement. In Eucalyptus plantations, continuous monitoring is critical to maximizing growth, enhancing paper production, and mitigating environmental damage. However, existing solutions face challenges in real-time monitoring due to factors such as parasitic interference, low-light conditions, and uneven terrain. In this work, we present a novel, end-to-end framework that enhances Eucalyptus tree measurement and monitoring. Our framework significantly improves data collection efficiency by allowing measurements at walking speed, reducing measurement distance by 50% compared to traditional manual approaches. This system integrates 2D-LiDAR with additional environmental sensors to extract key tree parameters, including circumference, position, and tree count. The collected data is stored in real-time and uploaded to a centralized server for further analysis. Experimental evaluations across 160 trees, under five distinct farm conditions, demonstrate that our system achieves 89% accuracy in tree diameter estimation and 98.5% accuracy in tree counting, significantly outperforming traditional methods. These results establish our framework as a highly effective solution for improving the accuracy and efficiency of tree monitoring in challenging environments.
Authors
- Mongkol Ekpanyapong (ORCID: https://orcid.org/0000-0002-0192-6249)
- Jednipat Moonrinta (ORCID: https://orcid.org/0000-0002-7918-007X)
- Matthew N. Dailey (ORCID: https://orcid.org/0000-0002-7191-3558)
- Pruek Vanna-Iampikul (ORCID: https://orcid.org/0000-0002-2897-7142)
- Visutr Boonnateephisit
- Somphop Limsoontharakul
Institutions
- Burapha University (TH)
- Prince of Songkla University (TH)
- Asian Institute of Technology (TH)
Publication Details
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1109/ieecon64081.2025.10987864
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00