News
Good start of year: two new UAV papers
In January 2022, two new research papers from two PhDs of the Unmanned Aerial Remote Sensing Facility have been published. The paper prepared by Norazlida Jamil was the first from her PhD research project: great milestone! The second paper was prepared by Gustavo Togeirode Alckmin and was the fourth and final paper as a result of his PhD research. Gustavo defended his PhD on May 19, 2021 at Wageningen University and as part of a double degree agreement he received his PhD also from the University of Tasmania. Below you can find more details on both papers and the PhD projects.
The PhD research of Norazlida is a joint project between the department of Farming Technology and the Laboratory of Geo-information Science and Remote sensing. The paper of Norazlida describes the applicability of UAV-based RGB imagery combined with the structure from motion (SfM) method for estimating the individual plants height of cabbage, pumpkin, barley, and wheat in an intercropping field during a complete growing season under varying conditions. This study suggests that UAV imagery can provide a reliable and automatic assessment of individual plant heights for cabbage and pumpkin plants in intercropping but cannot be considered yet as an alternative approach for barley and wheat. The results of her study are published in the journal Agriculture entitled ‘Evaluation of Individual Plant Growth Estimation in an Intercropping Field with UAV Imagery’. The paper is open-source and can be accessed through the following link: https://doi.org/10.3390/agriculture12010102
The PhD research of Gustavo was focussed on the scaling of field to airborne spectroscopy in combination with advanced spectral data analytics for accurate retrieval of perennial ryegrass biomass and feed quality. In his paper, he describes a two-year experiment comparing reflectance measurements between a handheld spectrometer and a commercial multispectral UAV camera. Different algorithms based on regression-tree architecture were contrasted regarding accuracy, speed, and model size. Model performances were validated, providing error-metrics for baseline accuracy and temporal validation. The results have shown that the standard procedure for multispectral imagery radiometric calibration is sub-optimal, requiring further post-processing and presenting low correlation with handheld measurements across spectral bands and dates. Nevertheless, after post-calibration, the use of spectral imagery has presented better baseline error than the point-based sensors. The results of his study are published in the journal Computers and Electronics in Agriculture entitled ‘Perennial ryegrass biomass retrieval through multispectral UAV data’. The paper is open-source and can be accessed through the following link: https://doi.org/10.1016/j.compag.2021.106574
Gustavo is currently working as Postdoctoral Fellow at the University of Missouri and continued his research on remote sensing of grasslands.