Abstract: To study the feasibility of extraction of maize lodging in plot area by UAV remote sensing. The authors obtained the digital surface model (DSM) of the study area by using the tilt photography method without the ground control points (GCPs) of a small unmanned aerial vehicle (UAV); the DSM was utilized as an additional feature together with the color features, i.e., red, green and blue color of the DOM, and then, the supervised classification method was performed on it to extract the maize lodging information; at last, we compared the results with the field survey results on the plot scale. The results showed that: the maize canopy height difference information represented by the digital surface model had a good complementarity with the image color characteristics, and the combination of the two could greatly improve the extraction accuracy of maize lodging information. Compared with the field survey data, the error of the number of lodging trees was only 4.44%, the error of plots number affected by lodging was 9.26%, and the error number of plots more than 85% was less than 5. Maize canopy height combined with color characteristic information can accurately extract lodging information of maize; the method of tilt photogrammetry can effectively reduce the intra-model distortion caused by the lack of ground control points and improve the working efficiency. This method provides a simple, rapid and effective means for the investigation of maize lodging in plot scale.