Horticultural Crop Management Facilitated by Drone Imagery

Agriculture is one of the research strengths of CQUniversity, and the Precision Horticulture sub-discipline is a field in which CQU has recently invested in staffing to build a strong team. To achieve optimum management practices and precise manipulation of crop production, future precision horticultural systems will require on-farm data collection across unprecedentedly broad spatial and temporal scales. As a cutting-edge technology, unmanned aviation vehicles (UAV) offers an efficient and economical way to gather a vast amount of crop and environment information, which can be applied in many aspects of the horticulture industry.

The Bundaberg region is one of the largest horticultural regions in Australia and an ideal location for precision horticulture research. UAV aerial imaging will support the following research fields to deliver important applications for local horticulture industries.

Protecting crop health from pests and diseases has been essential in research communities and industries. Rapid detection is vital to respond adequately, while delays can result in widespread pests and diseases, which can devastate local horticulture industries. However, conventional identification methods are often labour-intensive and may face crop accessibility problems in many cases (e.g. large tree crops). The UAV with thermal and multi-spectrum cameras will facilitate rapid and economical collection and analysis of crop spectral responses to detect pest and disease problems in the early stage, thereby helping farmers protect their crops.

The UAV system is also a highly efficient tool for crop status surveillance. Loaded with HD and multi-spectrum cameras, UAVs can collect image data from mapping various vegetation indexes (e.g. NDVI) and build 3D structures of crop canopies. This information will deliver many industry applications, such as predicting yield, assessing crop nutrient and water status, developing variable rate fertilisation schemes, and assessing irrigation system performance. These outputs will support the operation, management and decision-making of local industries.

Students interested in this research topic and who already have the skill sets below are encouraged to apply:

• Degree in a related field, such as biology, agriculture, environmental science or engineering.
• Related skills include remote sensing, GIS, image analysis, computer visualisation and digital photography.
• Experience in drone operation and engineering.