#$%^&*AU2020101709A420200917.pdf#####ABSTRACT The present invention relates to a crop yield prediction method and system based on low-altitude remote sensing information from an unmanned aerial vehicle (UAV). The method includes: obtaining a plurality of images taken by the UAV, where the UAV uses a multi-spectral camera to shoot crop canopies to obtain reflection spectrum images of a plurality of different bands； stitching the plurality of images to obtain a stitched image； performing spectral calibration on the stitched image to obtain the reflectivity of each pixel in the stitched image； using a threshold segmentation method to segment the stitched image, to obtain a target area for crop yield prediction； using a Pearson correlation analysis method to analyze a correlation between the reflectivity of each band and the growth status and yield of the crop to obtain feature bands； constructing yield prediction factors based on the feature bands； and determining a predicted crop yield value of the target area for crop yield prediction based on the yield prediction factors and a crop planting area of the target area for crop yield prediction. The present invention can improve the accuracy of crop yield prediction and reduce labor intensity.1/5 DRAWINGS 100 Obtain a plurality of images taken by a UAV 200 Stitch the plurality of images to obtain a stitched image 300 Perform spectral calibration on the stitched image based on a calibration coefficient of a spectral calibration plate to obtain the reflectivity of each pixel in the stitched image 1 _400 Use a threshold segmentation method to segment the stitched image based on the reflectivity of each pixel, to obtain a target area for crop yield prediction 41 500 Use a Pearson correlation analysis method to analyze a correlation between the reflectivity of each band and the growth status and yield of the crop to obtain feature bands 600 Construct yield pr
