Morphology-based approaches for detecting stream channels from ALSM data

Abstract

To map the Earth's surface at remarkable resolution, Airborne Laser Swath Mapping (ALSM) instrument technology and subsequent algorithms have been used over the last several years. Since forested watersheds have commonly been problematic to study with remote sensing techniques, the ability of ALSM technology to densely sample ground elevations beneath forest canopies is especially considerable. Stream network detection from digital elevation models (DEMs) is a key role in modelling spatially distributed hydrological processes. To detect stream channels, we have developed two approaches. The first approach is based on an encoding of mathematical morphological operators. In the second approach, a composition of geodesic top-hat and bot-hat operations of different sizes is used in order to build a morphological profile (P _M) that records the image structural information. The two proposed methods perform well in terms of detection results and classification accuracies. The second approach is more general than the first, but it also requires training and more computation.

Acknowledgements

The authors express their thanks to the NCALM, which acquired and processed the lidar data used in this research, and to Dr. Ramesh L. Shrestha and Bidhyananda Yadav for their comments. One of the authors, Dr. K. Clint Slatton, who was an associate professor of the Department of Electrical and Computer Engineering at the University of Florida, passed away on 30 March 2010; he will be with us in our hearts and minds.