UAV-based hyperspectral dataset for high-throughput yield phenotyping in wheat

Abstract

The dataset was collected by a hyperspectral camera (PIKA II, Resonon, Inc.) mounted on an unmanned aerial vehicle (UAV, DJI Matrice 600 Pro) from three experimental yield trial fields (C3, C4, and C9) during two consecutive growing seasons 2017 (C3 and C9) and 2018 (C4). The aerial hyperspectral images were captured within two weeks prior to harvest over 240 spectral channels in visible and near infrared region (400 nm to 900 nm) with about 2.1 nm spectral resolution and about 2 cm spatial resolution. Subsequent to radiometric calibration and noisy band removal, plots were cropped from the hyperspectral images and saved as 3D matrices with Matlab (MAT files) and Python (NPY files) format. The dataset entails hyperspectral cubes of 1021 wheat plots and the grain yield of plots harvested by a combine. The corresponding ground truth data (yield) for each hyperspectral cube representing a plot can be found based on the field (e.g., C3, C4, and C9) and plot ID.