Multispectral and thermal sensors attached to drones are becoming increasingly available for precision agriculture. For operational crop monitoring it’s important to explore the differences or complementary use of different sensors while also the effect of the diurnal differences in the data needs improved understanding. However, UAV-based datasets for testing the diurnal changes in real field conditions with multiple sensors are limited available. The company Aurea Imaging together with the Laboratory of Geo-information Science and Remote Sensing of Wageningen University, and the Plant Science Group of WUR have prepared and published an open and free drone data-set for testing the diurnal changes in real field conditions with multiple sensors in the Open Data Journal for Agricultural Research.
Next to image data, also field data have been acquired for geometrical and radiometric calibration. To co-register the entire dataset with high geometric accuracy we used 4 to 6 GCPs measured by an RTK-GPS. For radiometric validation purposes we measured the reflectance of 14 reference reflectance plates and 5 plant samples with field radiometers. These field datasets are also made available.
Christina Kallimani is first author of the paper, she prepared the paper and datasets together with Ramin Heidarian Dehkordi and Bert Rijk, all working for Aurea Imaging, and all three alumni of the MSc Geo-information Science of Wageningen University.
The results of the study and the complete dataset are published in the Open Data Journal for Agricultural Research in a paper entitled ‘UAV-based Multispectral & Thermal dataset for exploring the diurnal variability, radiometric & geometric accuracy for precision agriculture’
To explore the diurnal variations, radiometric and geometric accuracy of UAV-based data for precision agriculture, a comprehensive dataset was created in a one-day field campaign (21 June 2017). The multi-sensor data set covers wheat, barley & potato experimental fields, located in Wageningen University and Research (WUR) farm maintained by Unifarm. UAV-based images were collected with several sensors over the experimental area, starting from 7:25am and ending at 20:00pm local solar time. The dataset consists of images collected by 9 flights with senseFly MSP4C, 9 with Parrot Sequoia, 2 with Slant Range P3, 5 with DJI Zenmuse X3 NIR, 4 with the senseFly Thermo-map and 1 with the RGB Sony WX-220. Additionally, validation measurements at radiometric calibration plates and plant sample locations were taken with a Cropscan handheld spectrometer and a tec5 Handyspec spectrometer. The dataset consists of the validation measurements, the raw images and the processed orthomosaics (both with and without geometric correction).