Multi and hyperspectral UAV remote sensing: Grapevine phylloxera detection in vineyards

This paper describes field trials of Unmanned Aerial Vehicles (UAV) integrated with advanced digital hyperspectral and multispectral sensors to increase the efficiency of existing surveillance practices (human inspectors and insect traps) and application to detect a known endemic biosecurity pest (grape phylloxera) in Victorian vineyards. We evaluated airborne RGB, multi and hyperspectral imagery at two different vineyards with multiple grapevine varieties, in two separate time periods and under different levels of phylloxera infestation. The methods used to incorporate the sensors to the UAV, the flight operations and the processing workflow of the datasets from each imagery type are described. The ultimate aim of this study is to create an integrated methodology for collecting and processing multi and hyperspectral data with the purpose of remote sensing different variables in different applications such as, in this case, plant biosecurity. The development of a methodology for the collection and analysis of airborne multi and hyperspectral imagery would provide scientists with reliable data collection protocols and faster processing techniques to achieve different remote sensing objectives.