Cano, E.; Horton, R.; Liljegren, C.; Bulanon, D. Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing. Journal of Imaging 2017, 3, 4, doi:10.3390/jimaging3010004.
Cano, E.; Horton, R.; Liljegren, C.; Bulanon, D. Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing. Journal of Imaging 2017, 3, 4, doi:10.3390/jimaging3010004.
Cano, E.; Horton, R.; Liljegren, C.; Bulanon, D. Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing. Journal of Imaging 2017, 3, 4, doi:10.3390/jimaging3010004.
Cano, E.; Horton, R.; Liljegren, C.; Bulanon, D. Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing. Journal of Imaging 2017, 3, 4, doi:10.3390/jimaging3010004.
Abstract
Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV) have paved the way to accessible remote sensing tools for farmers. This paper describes the comparison of two popular off-the-shelf sUAVs: 3DR Iris and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every second for two minutes. The position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. Results showed that both sUAV performed well in both the hovering test and the rectilinear motion test. This demonstrates that both sUAVs can be used for agricultural monitoring.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.