Disclosed a crop yield prediction method and system based on low-altitude remote sensing information from an unmanned aerial vehicle (UAV). Obtaining a plurality of images taken by the UAV; 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.