Effects of solar elevation angle on the visible light vegetation index of a cotton field when extracted from the UAV

作者：Jiancheng Li, Weimo Wu, Changwei Zhao, Xinlu Bai, Lijun Dong, Yu-Jie Tan, MaYira Yusup, Guliye Akelebai, Helin Dong, Jinhu Zhi · 发表于：Scientific Reports · 年份：2025 · DOI：10.1038/s41598-025-00992-6 · 被引用次数：13 · 研究领域：Remote Sensing in Agriculture、Remote Sensing and LiDAR Applications、Impact of Light on Environment and Health

The visible light vegetation indices (VIs) derived from the red, green, and blue spectral bands of UAV (unmanned aerial vehicle) imagery play a vital role in precision agriculture applications. Nevertheless, the effects of solar elevation angle variations across different flight times remain poorly understood. The DJI Phantom 4 RTK high-precision positioning aerial survey UAV was used to conduct a timed flight over cotton plots with both weak growth without nitrogen application and strong growth with nitrogen application. The visible light VIs for 13 UAVs at 12 different flight times were extracted, and a one-dimensional linear regression model established. By comparing the difference significance and slope values of the models, to evaluate the influence degree of solar elevation angle and cotton growth on the visible light VIs of 13 kinds of UAV, so as to provide a reference for the reasonable planning of UAV flight time under the background of precision agriculture. The results show that: (1) No matter in the test plots with relatively weak or prosperous cotton growth, Solar elevation angle was always significantly positively correlated with the excess red vegetation index (ExR) and red-green ratio index (RGRI). There was a significant linear negative correlation with the excess green minus excess red vegetation index (ExGR), excess green vegetation index (ExG), red-green-blue vegetation index (RGBVI), modified green-red vegetation index (MGRVI), green leaf index (GLI), nor...