Abstract: In order to analyze the deformation status and development trend along the Changjiang River, and to maintain flood control safety and river regime stability, SBAS-InSAR technology was utilized to monitor ground deformation with 61 Sentinel-1A images covering the Changjiang River riparian area of Nanjing reach from March 2017 to March 2022.Additionally, the long short-term memory neural network model(LSTM) was used to predict the future trend of feature points.The results revealed that:(1) Compared with the leveling monitoring results, the accuracy of SBAS-InSAR was verified.The average annual ground deformation rate in the study area ranged from-31～19 mm/a, and four subsidence funnels were formed along the Changjiang River in Nanjing reach.(2) The deformation prediction values of LSTM model exhibited a high degree of consistency with the SBAS-InSAR results, with a maximum absolute error of 3.28 mm.Using LSTM to predict the subsidence trend of feature points in the study area, it is found that the overall trend in the next 2 years will involve slow subsidence and a tendency to stabilize.The results can provide technical reference for relevant departments formulating protection and planning plans for the Changjiang River riparian area.