Abstract: River wading is a major cause of natural disasters in the lower reaches of the Yellow River, and the analysis of its wading pattern is of great significance for the protection of settlements and farmlands in the downstream beach areas. Aiming at the river loitering problem in the lower Yellow River, this paper proposes a PCA-SVM extraction method for the Yellow River channel by using the multi-source long time series of domestic satellites, and interpretes the river channel information of the Puyang section of the Yellow River from 2013 to 2022, and takes the Lotus node channel as an example to analyze its loitering trend. The results show that the Yellow River channel extracted by PCA-SVM method is complete and the sand bar is clear, which significantly improves the classification confusion of the river channel, wetland and tidal flat, and the interpretation accuracy is 84.17%. The Kappa coefficient is 0.613, and the accuracy is significantly higher than that of maximum likelihood classification, minimum distance classification and SVM. Through the analysis of the loitering trend of the Yellow River from 2013 to 2022, it can be seen that the loitering trend of the lotus node channel in the study area is obvious, and the main channel has migrated from the left bank to the right side, and there is still a loitering and migration trend to the right by August 2022. The erosion of residential areas and farmland in the right bank beach area is intensified, which is easy to cause dangerous workers and lead to flood disasters.

Key words: lower Yellow River, wandering reaches, remote sensing, PCA-SVM, flood hazards