V. S. G. Raghavan, L. Gobeawan, C. W. Lim, X. Liu, J. Chat- toraj, and F. Yang, “Detecting plant tropism from LiDAR data,” in 10th International Conference on Functional-Structural Plant Models (FSPM2023) (T.-W. Chen, A. F. K. Kahlen, and H. Sttzel, eds.), pp. 123–124, Mar 2023
Abstract:
Understanding plant tropism is crucial in planning for a successful plant cultivation, although detecting plant tropism is commonly done on young, small plants in a controlled environment. It is not trivial to measure tropism on mature street trees without elaborate setups or techniques. However, it will be very useful to capture the tropism information of mature street trees for environmental analysis and simulation purposes, e.g., root-soil condition, shading, tree pruning, etc.. With the abundance of urban LiDAR scan data in Singapore, measuring plant tropism of mature street trees from LiDAR data can be attained. We propose a methodology to measure plant tropism effects directly from LiDAR data without field observation work.
License type:
Publisher Copyright
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