Development of a LiDAR-guided section-based tree canopy density measurement system for precision spraying

Project Type: Graduate Student
Funds awarded in 2020: $15,000.00
Projected End Date: 10/31/2022
Grant Recipient: The Pennsylvania State University
Region: Northeast
State: Pennsylvania
Graduate Student:
Faculty Advisor:
Long He
Pennsylvania State University
A ground-based canopy density measurement system to support precision spraying in apple orchards was developed to precisely apply pesticides to orchard canopies. The automated measurement system was comprised of a light detection and ranging (LiDAR) sensor, an interface box for data transmission, and a laptop computer. A data processing and analysis algorithm was developed to measure point cloud indices from the LiDAR sensor to describe the distribution of tree canopy density within four sections according to the position of the trellis wires. Experiments were conducted in two orchard sites, one with GoldRush (larger trees) and the other one with Fuji (smaller trees) apple trees. Tree leaves were counted manually from each section separated by trellis wires. Field evaluation results showed a strong correlation of 0.95 (R2 = 89.30%) between point cloud data and number of leaves for the Fuji block and a correlation of 0.82 (R2 = 67.16%) was obtained for the GoldRush block. A strong correlation of 0.98 (R2 = 95.90%) was achieved in the relationship between canopy volume and number of leaves. Finally, a canopy density map was generated to provide a graphical view of the tree canopy density in different sections. Since accurate canopy density information was computed, it is anticipated that the developed prototype system can guide the sprayer unit for reducing excessive pesticide use in orchards.
Peer-reviewed Journal Article
Md Sultan Mahmud, The Pennsylvania State University
Azlan Zahid, The Pennsylvania State University
Long He, The Pennsylvania State University
Daeun Choi, The Pennsylvania State University
Grzegorz Krawczyk, The Pennsylvania State University
Heping Zhu, USDA-ARS
Paul Heinemann, The Pennsylvania State University
Target audiences:
Farmers/Ranchers; Educators; Researchers; Consumers
Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.