The Effect of LiDAR Digital Elevation Model Resolution on Stream Network Prediction and Computational Requirements

Abstract

Mouton will describe his research into stream prediction. In his study, he examined the effects of digital elevation model (DEM) grid size for stream network predictions in the northwestern United States to test the accuracy of high-resolution LiDAR (Light Detection and Ranging) digital elevation data. He will describe the elevation data and routing algorithms used. He will also discuss the results of his analyses. His study illustrates the potential of LiDAR to accurately predict perennial flow in a given landscape. The ability to locate fish barriers based on landscape gradient also improved with LiDAR data. As LiDAR datasets become more available, automated creation of stream networks and their hydrologic features will become more feasible and the accuracy of the results will be much improved.