Evaluation of a UAV-mounted consumer grade camera with different spectral modifications and two handheld spectral sensors for rapeseed growth monitoring: Performance and influencing factors

Authors: ZHANG, JIAN - Huazhong Agricultural University; WANG, CHUFENG - Huazhong Agricultural University; Yang, Chenghai; JIANG, ZHAO - Huazhong Agricultural University; ZHOU, GUANGSHENG - Huazhong Agricultural University; WANG, BO - Huazhong Agricultural University; SHI, YEYIN - University Of Nebraska; ZHANG, DONGYAN - Anhui Agricultural University; YOU, LIANGZHI - International Food Policy Researc Institute (IFPRI); XIE, JIANG - Huazhong Agricultural University

Submitted to: Precision Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/27/2020
Publication Date: 2/10/2020
Citation: Zhang, J., Wang, C., Yang, C., Jiang, Z., Zhou, G., Wang, B., Shi, Y., Zhang, D., You, L., Xie, J. 2020. Evaluation of a UAV-mounted consumer grade camera with different spectral modifications and two handheld spectral sensors for rapeseed growth monitoring: Performance and influencing factors. Precision Agriculture. https://doi.org/10.1007/s11119-020-09710-w.
DOI: https://doi.org/10.1007/s11119-020-09710-w

Interpretive Summary: Consumer-grade cameras provide a low-cost imaging tool for precise crop monitoring, but few studies have examined the accuracy and effectiveness of modified consumer-grade cameras with different spectral filters. This study evaluated the performance of a consumer-grade camera fitted sequentially with seven visible and near-infrared (NIR) filters. The camera was mounted on an unmanned aerial vehicle (UAV) to collect aerial images over a rapeseed field for comparison with data from ground-based spectral sensors. Spectral and statistical analysis results showed that the quality of the NIR band images was inferior to that of the visible bands and that the vegetation indices derived from the visible bands were as effective as those from the handheld spectral data for assessing rapeseed growth parameters. The results from this study provide useful information on the selection of appropriate filters for camera modifications to ensure image quality and sensitivity for precise crop monitoring.

Technical Abstract: The objective of this study was to evaluate the crop monitoring performance of a consumer-grade camera with non-modified and modified spectral ranges which are commonly used in low-altitude unmanned aerial vehicles (UAVs). The camera was fixed sequentially with seven types of filters for collecting visible images and near-infrared (NIR) images with different center band locations and bandwidths. Meanwhile, field-based hyperspectral data and normalized difference vegetation index (NDVI) measured by a GreenSeeker handheld crop sensor (GS-NDVI) were collected to examine the accuracy of rapeseed growth monitoring in terms of VIs derived from UAV images. Results showed that the UAV-based RGB-VIs and optimal NIR-VIs had similar accuracy for predicting GS-NDVI. Moreover, similar results were achieved based on the hyperspectral data, indicating the importance of spectral characteristics for GS-NDVI estimation. However, the UAV-based results also indicated that the performance of VIs derived from the band combinations containing longer NIR center wavelengths and narrower bandwidths was obviously poorer than that of the RGB-VIs. The image quality of the NIR band was also found to be inferior to the visible bands based on quantitative analysis, which also revealed that image quality had great impact on UAV-based results. Image quality was then related to the effects of camera exposure, spectral sensitivity, soil background and dark areas. The results from this study provide useful information for camera modifications by selecting appropriate filters that not only are sensitive to crop growth, but also ensure image quality.