Optimising drone flight planning for measuring horticultural tree crop structure
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Hydrology, Agriculture and Land Observation Group, Water Desalination and Reuse Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
Water Desalination and Reuse Research Center (WDRC)
Online Publication Date2019-12-18
Print Publication Date2020-02
Embargo End Date2021-05-05
Permanent link to this recordhttp://hdl.handle.net/10754/660966
MetadataShow full item record
AbstractIn recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties.
CitationTu, Y.-H., Phinn, S., Johansen, K., Robson, A., & Wu, D. (2020). Optimising drone flight planning for measuring horticultural tree crop structure. ISPRS Journal of Photogrammetry and Remote Sensing, 160, 83–96. doi:10.1016/j.isprsjprs.2019.12.006
SponsorsThis research was funded by Department of Agriculture and Water Resources, Australian Government and Horticulture Innovation Australia as part of its Rural R&D for Profit Program's subproject “Multi-Scale Monitoring Tools for Managing Australia Tree Crops - Industry Meets Innovation” [grant number RnD4Profit-14-01-008].