Use of LiDAR Data for Parameterization of Functional-Structural Plant Models
By Vera Bekkers
Functional-Structural Plant (FSP) models are useful tools for understanding plant functioning and how plants react to their environment. Developing tree FSP models is data-intensive and measuring tree architecture using conventional measurement tools is a laborious process. Light Detection and Ranging (LiDAR) could be an alternative non-destructive method to obtain structural information. This research aimed to investigate how TLS LiDAR-derived tree traits could
be used for tree FSP models by providing model inputs. A summary of tree parameters needed for FSP model development was made through a systematic literature search. A total of 90 papers on FSP tree models were screened and 8 papers fulfilled all the selection criteria. From these papers, 45 structural parameters used for FSP model development were identified, from which 26 parameters were found to be derivable from LiDAR. Furthermore, a tropical tree and Scots pine FSP model were selected and parametrized with LiDAR-derived parameters. The model inputs were compared with the results of the systematic literature review to identify parameters derivable from LiDAR. Internode length and branch angle were identified to be possible and Quantitative Structural Models (QSM) were used to derive the parameters. A total of 37 LiDAR-scanned tropical trees and 20 Scots pines were used for the study. The LiDAR-derived
parameters were compared to measurements, and it was found that the accuracy was variable. The LiDAR-derived internode length and branch angle were used as inputs for the two FSP models. It was found that branch angle could be used as model input, but internode length was unsuitable. Outputs of the FSP models with LiDAR-derived branch angle differed from the FSP model outcomes with default branch angle. Results showed that it is possible to use LiDAR
for FSP model inputs, although caution is needed as the implications on model outcomes need further investigation.
Keywords: LiDAR; Terrestrial Laser Scanner; Functional-Structural Plant models; Quantitative Structural Models