Automatic Recognition of Rivers from Lidar Data by Profile Factor

Laser infrared Detection and Ranging (LiDAR) has become one competitive remote sensing (RS) and photogrammetry technique. Extracting rivers’ distribution from LiDAR’s point cloud is one of its important research directions. But traditional methods are not completely suitable for the ranging data of LiDAR. Novel algorithm with profile factor as the kernel circle is proposed for rivers’ automatic recognition. Image unification, edge extraction and skeleton generation are the premier three steps. The profile factor of morphology can be expressed as shape functions for concrete judgement. Natural rivers’ profile is like “U” form, and artificial water-body’s can be simplified as “M” figure. While highway’s section can be considered as “W” shape. Then corresponding profile factor functions (PFF) can be established for determination. The experimental comparisons show that the results by the proposed algorithm are close to which from high-resolution RS images by manual interpretation. * Corresponding author.