Research on soybean seedling number estimation based on UAV remote sensing technology

In order to improve the timeliness and accuracy of soybean seedling number estimation, a soybean seedling number estimation method based on the unmanned aerial vehicle（UAV） remote sensing technology was proposed. Unmanned aerial vehicle（UAV） was used to obtain images of soybean seedlings, different vegetation indices, and histogram equalization. The Otsu threshold algorithm was selected to extract soybean targets. Outlier removal and morphological algorithm were used to remove weed noise. The connected region analysis method was used to estimate the soybean seedling number. Combined with the field measured data, a linear regression model was established between the measured seedling number and the estimated seedling number. By comparing the extraction results of soybean targets with different methods, it is shown that the Otsu threshold algorithm combined with the over-green index has a better effect on soybean image segmentation. The linear regression model of the measured seedling number and the estimated seedling number has a high degree of fit. The correlation coefficient R~2 was 0.909 4, and the average error of emergence statistics was 0.43%. The method has a low error. Soybean seedling numbers can be quickly and accurately identified. It can provide theoretical reference for agricultural producers to obtain information on soybean seedling situations intelligently.