C. W. Lim, X. Liu, L. Gobeawan, V. S. G. Raghavan, J. Chat- toraj, and F. Yang, “Species model parameterisation,” in 10th International Conference on Functional-Structural Plant Mod- els (FSPM2023) (T.-W. Chen, A. F. K. Kahlen, and H. Sttzel, eds.), pp. 68–69, Mar 2023
Abstract:
Species modelling from remote sensing data for digital twin cities is increasingly important to enable digital tree management, environmental simulations and analysis for urban planning. Species modelling for large, city scale involves parameterisation of various traits of individuals and species into an individual profile and species profile, respectively. A species profile is used to generate individual tree models of certain species, whereas an individual profile is used to generate a unique individual species model. Both profiles are derived from extracting or estimating parameter values (known parameters) from field observation and remote sensing data (such as LiDAR point cloud) and solve for unknown parameters by optimisation. This work aims to describe and demonstrate a workflow of species model parameterisation from point cloud data to optimised individual species model.
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Funding Info:
This research / project is supported by the National Research Foundation, Singapore - Joint New Zealand - Singapore Data Science Research Programme
Grant Reference no. : SDSC-2020-002