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Unmanned aerial vehicles (UAVs) equipped with lightweight spectral sensorsfacilitate non-destructive, near-real-time vegetation analysis. In order toguarantee robust scientific analysis, data acquisition protocols andprocessing methodologies need to be developed and new sensors must becompared with state-of-the-art instruments. Four different types of opticalUAV-based sensors (RGB camera, converted near-infrared camera, six-bandmultispectral camera and high spectral resolution spectrometer) weredeployed and compared in order to evaluate their applicability forvegetation monitoring with a focus on precision agricultural applications.Data were collected in New Zealand over ryegrass pastures of variousconditions and compared to ground spectral measurements. The UAV STSspectrometer and the multispectral camera MCA6 (Multiple Camera Array) were found to deliverspectral data that can match the spectral measurements of an ASD at groundlevel when compared over all waypoints (UAV STS: R2=0.98; MCA6:R2=0.92). Variability was highest in the near-infrared bands for bothsensors while the band multispectral camera also overestimated the greenpeak reflectance. Reflectance factors derived from the RGB (R2=0.63)and converted near-infrared (R2=0.65) cameras resulted in loweraccordance with reference measurements. The UAV spectrometer system iscapable of providing narrow-band information for crop and pasturemanagement. The six-band multispectral camera has the potential to bedeployed to target specific broad wavebands if shortcomings in radiometriclimitations can be addressed. Large-scale imaging of pasture variability canbe achieved by either using a true colour or a modified near-infrared camera.Data quality from UAV-based sensors can only be assured, if field protocolsare followed and environmental conditions allow for stable platformbehaviour and illumination

Deploying four optical UAV-based sensors over grassland: challenges and limitations