Open AccessUAV-based Multispectral & Thermal dataset for exploring the diurnal variability, radiometric & geometric accuracy for precision agriculture
Author(s) -
Christina Kallimani,
Ramin Heidarian,
F.K. van Evert,
Bert Rijk,
Lammert Kooistra
Publication year - 2020
Publication title -
open data journal for agricultural research
Language(s) - English
Resource type - Journals
ISSN - 2352-6378
DOI - 10.18174/odjar.v6i0.16317
Subject(s) - multispectral image , remote sensing , rgb color model , radiometric calibration , precision agriculture , calibration , environmental science , radiometry , spectrometer , computer science , geography , computer vision , mathematics , optics , agriculture , statistics , physics , archaeology
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).