Estimation of wheat planting density using UAV image

doi:10.6046/gtzyyg.2020.04.16

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Abstract

Wheat is a densely planted crop, and the planting volume per acre is nearly 20 kg. The plant density of winter wheat will directly affect the final yield. Therefore, real-time monitoring of wheat plant density is an important way to ensure wheat yield. At present, the main method for obtaining the plant density of wheat is mainly manual measurement, which is time-consuming and laborious. In this paper, the DJ inspire 2 UAV is equipped with a Zens X4S camera to obtain high-resolution visible light images of wheat planting areas, extract wheat coverage based on UAV images, and establish the relationship between plant density and plant density so as to achieve rapid acquisition of wheat plant density based on UAV image. Experiments show the following results: ① Using the improved HSI color model to extract wheat coverage improves accuracy and extraction efficiency compared with traditional visual estimation, manual counting and other classification methods, and overcomes differences in lighting conditions and shadows of different sorts of UAV images influences. ② There is a high correlation between wheat coverage and plant density at the seedling stage, overwintering stage and turning green stage. Among them, the correlation coefficient R² between the coverage based on drone image and the plant density of wheat are 0.737 9, 0.898 1 and 0.897 6 in three growth stages. The verification results of the relationship model using Niutengyu Village samples show that the inversion results based on the established relationship model also have a good correlation with the measured values, and R² reaches 0.919 8.

Keywords wheat UAV image vegetation cover planting density HSI color model Hough transform

TP79

Corresponding Authors: SU Wei E-mail: wangwei007@cau.edu.cn;suwei@cau.edu.cn

Issue Date: 23 December 2020

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	Wei WANG
	Xinsheng WANG
	Chan YAO
	Tian JIN
	Jiayu WU
	Wei SU

Cite this article:

Wei WANG,Xinsheng WANG,Chan YAO, et al. Estimation of wheat planting density using UAV image[J]. Remote Sensing for Land & Resources, 2020, 32(4): 111-119.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.04.16 OR https://www.gtzyyg.com/EN/Y2020/V32/I4/111

Fig.1 Study area and zoomed UAV image

Tab.1 Time and flight parameters for UAV image acquisition

Fig.2 In-situ taken picture of wheat plants

Fig.3 Workflow for estimating wheat plant density and seedling deficiency rate using UAV image

Fig.4 Process of wheat plant density estimation based on UAV images and field data

Fig.5 Correlation between the computed vegetation coverage and the measured plants

Fig.6 Correlation between wheat coverage and planting density using average ridge spacing and UAV image

Fig.7 Accuracy of estimated wheat planting density with in-situ measured density

Fig.8 Calculated seedling shortage rate (zoomed)

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