High-precision plant height measurement by drone with RTK-GNSS and single camera for real-time processing

Abstract

Conventional crop height measurements performed using aerial drone images require the 3D reconstruction results of several aerial images obtained through structure from motion. Therefore, they require extensive computation times and their measurement accuracy is not high; if the 3D reconstruction result fails, several aerial photos must be captured again. To overcome these challenges, this study proposes a high-precision measurement method that uses a drone equipped with a monocular camera and real-time kinematic global navigation satellite system (RTK-GNSS) for real-time processing. This method performs high-precision stereo matching based on long-baseline lengths during flight by linking the RTK-GNSS and aerial image capture points. A new calibration method is proposed to further improve the accuracy and stereo matching speed. Throught the comparison between the proposed method and conventional methods in natural world environments, wherein it reduced the error rates by 62.2% and 69.4%, at flight altitudes of 10 and 20 m. Moreover, a depth resolution of 1.6 mm and reduction of 44.4% and 63.0% in the errors were achieved at an altitude of 4.1 m, and the execution time was 88 ms for images with a size of 5472 × 3468 pixels, which is sufficiently fast for real-time measurement.

Plant phenotyping relevance

ドローン画像とRTK-GNSSを用いた植物高のリアルタイム測定法を開発し、既存法との精度・速度比較で検証しており、表現型取得手法が中心である。

Code and data availability

The preprint declares that the datasets generated/analysed (drone images, GNSS data, and phenotyping measurements) are publicly available in the authors' supplementary materials zip archive. The Middlebury stereo dataset is a generic external resource, not paper-specific.