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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Research Unit » Research » Publications at this Location » Publication #337083
Title: Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data

Author
item BAILEY, BRIAN - University Of California
item Mahaffee, Walter - Walt

Submitted to: Measurement Science and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/30/2017
Publication Date: 5/11/2017
Citation: Bailey, B.N., Mahaffee, W.F. 2017. Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data. Measurement Science and Technology. 28(6):064006. doi: 10.1088/1361-6501/aa5cfd.

Interpretive Summary: Detailed information on leaf area and orientation is needed to improve our understanding of how plant canopies influence air flow and solar radiation absorption in agriculture, natural, and urban environments. However, using current methods this information requires extensive time commitment and is prone to high error rates. There is a critical need for a technique that can rapidly measure the leaf area and orientation in space and time in order to improve our understanding of air flow and solar radiation interception to estimate crop growth, yields, water use, carbon sequestration, and heating and cooling demands. A new method was developed to simultaneously measure leaf orientation and leaf area using terrestrial LiDAR data. The method was validated by comparing LiDAR-measured leaf area to 1) 'synthetic' or computer-generated LiDAR data where the exact area was known, and 2) direct measurements of leaf area in the field using destructive sampling. Overall, agreement between the LiDAR and reference measurements was very good, showing a normalized root-mean-squared-error of about 15% for the synthetic tests, and 13% in the field.

Technical Abstract: The rapid evolution of high performance computing technology has allowed for the development of extremely detailed models of the urban and natural environment. Although models can now represent sub-meter-scale variability in environmental geometry, model users are often unable to specify the geometry of real domains at this scale given available measurements. As one of many examples, this work focuses on the measurement of geometry associated with trees. An emerging technology in this field has been the use of terrestrial LiDAR scanning data to rapidly measure the three-dimensional distribution of leaf area. However, such methods suffer from the limitation that they require detailed knowledge of leaf orientation in order to translate projected leaf area into total (or actual) leaf area. Common methods for measuring leaf orientation are often tedious or inaccurate, which places constraints on the LiDAR measurement technique. This work presents a new method to simultaneously measure leaf orientation and leaf area within an arbitrarily defined volume using terrestrial LiDAR data. The method was validated by comparing LiDAR-measured leaf area to 1) 'synthetic' or computer-generated LiDAR data where the exact area was known, and 2) direct measurements of leaf area in the field using destructive sampling. Overall, agreement between the LiDAR and reference measurements was very good, showing a normalized root-mean-squared-error of about 15% for the synthetic tests, and 13% in the field.