Using Non-Infrared UAV Imagery To Assess The Health of Dairy Farming Pasture

Stephens, Kristopher (2018) Using Non-Infrared UAV Imagery To Assess The Health of Dairy Farming Pasture. [USQ Project]


Abstract

Life on a dairy farm requires continuous monitoring and management of not only livestock health, but also vegetation health. Dairy farming is a lifestyle and industry heavily dependent on the natural elements, which can impact positively and negatively on the success of a dairy farm’s vegetation. When dairy farmers have access to effective vegetation management resources, they are better able to monitor, adapt and provide a pasture of high quality all year round. Unmanned Aerial Vehicles (UAV) fitted with expensive infrared cameras or filters are the most popular and effective way to monitor vegetation health. Alternatively, indices that utilise visible light, where no modification to a standard UAV is needed, provide an inexpensive option for dairy farmers to also determine the overall health of their pasture.

The research undertaken in this paper will attempt to address whether a standard UAV, using visible vegetation indices, will be able to effectively monitor pasture within an operational dairy farm. It is hoped that this will assist the farmer in pasture management decisions and rotating cattle around the farm.

The methodology for the research focused on not only assessing the reliability of the indices, but also determining the extent to which this form of pasture monitoring and management would be achievable and effective as a whole process. A UAV flight was performed to include the entirety of the farm, with biomass samples measured for comparison, ensuring each paddock and its varying pasture was included in the research. Once processed, the data provided a quantitative assessment of how accurately the chosen vegetation indices could monitor the pasture. Assessing in a way that was applicable to ordinary dairy farmers, such as flying the UAV over the whole farm and trying to be as cost effective as possible also carried out a qualitative approach.

Results suggested that one vegetation index was more reliable than the other. The Visible Atmospheric Reflection Index (VARI) was deemed to be more dependable than the Triangular Greenness Index (TGI) when assessing dairy farming pasture. However, it was determined that in order for dairy farmers to effectively utilize this process as a pasture measuring tool in a way that is beneficial to the ongoing operations of the farm, a number of obstacles still need to be overcome.

It is hoped that the research will extend on previous studies into UAV applications within working dairy farms. This is the first known investigation into the utilisation of visible vegetation indices within the dairy farming setting and it is hoped that it will provide a stepping-stone for further research.


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Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Spatial Science (Honours)(Surveying)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Supervisors: Gharineiat, Zahra
Date Deposited: 10 Sep 2021 05:54
Last Modified: 10 Sep 2021 05:54
URI: http://eprints.usq.edu.au/id/eprint/40652

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