Abstract
Current algorithms that deduce the drainage network from a digital elevation model (DEM) represented by a regular array of surface elevations share a fault: Unless the terrain is rugged, the derived water channels tend to flow in parallel lines along preferred directions engendered by the sampling grid orientation. We present a simple solution to the problem. A second difficulty is the presence of noise that creates artificial pits. We briefly describe a method which deals with pits in what we believe to be a more efficient manner for virtual memory environments than previous efforts. Our system has treated DEMs of nearly 9,000,000 pixels. We show how depth first search of the resulting drainage network permits segmentation of the DEM into basins by various criteria, analysis of stream‐sediment anomaly dilution profiles, improved hydrological models and other applications.
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