*4.7. Shortcoming and Prospects of Research*

Although the new crop lodging identification method proposed in this paper has good stability and high accuracy in complicated field conditions, its universality at the regional scale requires further exploration and verification. When applied to satellite images, the accuracy of the new method may decrease due to the following factors: (1) the spatial resolution and image quality of satellite images are lower than those of UAV images; (2) satellite images include more non-vegetation objects, includinghouses,otherlodgings,andlakes;and(3)detailedCSFcannotbeobtainedfromsatelliteimages.

Compared with the multispectral camera, the three-dimensional cloud points obtained by LiDAR have higher density and accuracy, which would improve the accuracy of CSF and lodging identification. In the future, we could use UAVs equipped with hyperspectral sensors to obtain hyperspectral images with abundant spectral information, allowing more vegetation index features to be constructed. Moreover, the relationship between background factors and lodging crops should be fully analyzed to determine the main factors that cause lodging.
