Articles
Modeling 3D architecture of adult peach trees (Prunus persica (L.) Batsch) using remote sensing data
Article number
1360_37
Pages
307 – 314
Language
English
Abstract
Peach fruits are a worldwide commodity used either in the fresh fruit market or in the food processing industry.
However, growers need to evaluate tree traits to enable precision orchard management decisions.
In this regard, a combination of remote sensing data with computational models capable of estimating canopy volume can be valuable to growers, especially for cultural practices such as spraying and pruning that can enhance yield and fruit quality.
In our ongoing work, the overall objective was to obtain 3D architecture models of adult peach trees (Prunus persica (L.) Batsch) to further inferences about their canopy structure.
Ground reference and remote sensing data were acquired from peach trees from a research orchard in Pullman, WA, USA. The RGB imagery was collected from a quadcopter at 15 m of altitude using three different sensor angles (45°, 65°, and 90°) and the light detection and ranging (LiDAR) data were obtained tree by tree at ground level.
Canopy height model (CHM) was utilized to estimate the tree height, crown area, and volume.
Correlation analysis indicated that the digital traits such tree height and volume were strongly correlated with manual measurements and LiDAR data.
The integrated data (CHM developed from digital surface model combining the data acquired at different sensor angles) showed best results and may be of more practical use for growers.
However, growers need to evaluate tree traits to enable precision orchard management decisions.
In this regard, a combination of remote sensing data with computational models capable of estimating canopy volume can be valuable to growers, especially for cultural practices such as spraying and pruning that can enhance yield and fruit quality.
In our ongoing work, the overall objective was to obtain 3D architecture models of adult peach trees (Prunus persica (L.) Batsch) to further inferences about their canopy structure.
Ground reference and remote sensing data were acquired from peach trees from a research orchard in Pullman, WA, USA. The RGB imagery was collected from a quadcopter at 15 m of altitude using three different sensor angles (45°, 65°, and 90°) and the light detection and ranging (LiDAR) data were obtained tree by tree at ground level.
Canopy height model (CHM) was utilized to estimate the tree height, crown area, and volume.
Correlation analysis indicated that the digital traits such tree height and volume were strongly correlated with manual measurements and LiDAR data.
The integrated data (CHM developed from digital surface model combining the data acquired at different sensor angles) showed best results and may be of more practical use for growers.
Authors
S. Sankaran, E.F. Carlos, M.G. Raman
Keywords
unmanned aerial vehicle, LiDAR, tree height, canopy crown volume, sensor angle
Groups involved
- Division Precision Horticulture and Engineering
- Division Plant-Environment Interactions in Field Systems
- Division Vine and Berry Fruits
- Division Tropical and Subtropical Fruit and Nuts
- Division Plant Genetic Resources, Breeding and Biotechnology
- Division Temperate Tree Nuts
- Division Temperate Tree Fruits
- Division Vegetables, Roots and Tubers
- Division Sustaining Horticulture in a Changing World
- Working Group Mechanization, Digitization, Sensing and Robotics
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