This paper firstly explores and applies the newly low-altitude airborne LiDAR technology to solve the mapping problem of the middle-lower Yangtze River Riparian zone covered with multi-layer and high-density vegetation. A vegetation filtering algorithm is proposed for the low-attitude airborne LiDAR point clouds collected in the complex area with multi level and dense vegetation coverage. After the coarse filtering of point clouds by multi-echo analysis, this algorithm extracts the ground seed points by morphological calculation, fits the trend surface of the local terrain, then eliminates the vegetation points and preserves the ground points using the Random Sample Consensus, thereby acquiring the DEM of measured area. The experimental results show that the proposed algorithm can intelligently remove the vegetation point clouds in the middle-lower Yangtze River riparian zone, where topographic relief is large and vegetation cover is dense. This research also shows that by designing a special filtering approach, it is possible to classify laser points into terrain and vegetation automatically even for thoroughly mixed vegetation and terrain points with low penetration rate of below 15%.