GeoNet Geomorphologically Relevant Image Processing

Today’s high resolution topography data presents new opportunities for geomorphologic research in the area of environmental prediction and hazard assessment. To use this data for such research, NCED scientists created a new computational tool: GeoNet. GeoNet extracts channels and channel networks from high resolution digital elevation data. During the extraction process, GeoNet incorporates nonlinear filtering, for the initial preprocessing of data, and energy minimization principles, for feature extraction. The use of nonlinear filtering, with a variable diffusion coefficient, achieves noise removal (in low gradient areas) and edge enhancement (in high gradient areas, ie, feature boundaries). After this preprocessing, GeoNet extracts channels as geodesics—lines that minimize a cost function, which is based on the fundamental geomorphologic characteristics of channels, such as flow accumulation and curvature. Right now, GeoNet performs only channel extractions. However, by varying the cost function, future versions of GeoNet will allow users to select other geomorphic features of interest, such as landslides, service roads, terraces, etc. GeoNet, another tool for NCED’s toolbox, represents an example of successful, interdisciplinary collaboration among geomorphologists, mathematicians, and image processing experts.

References

Passalacqua, P., T. Do Trung, E. Foufoula-Georgiou, G. Sapiro, and W. E. Dietrich, A geometric framework for channel network extraction from LiDAR: nonlinear diffusion and geodesic paths, J. Geophys. Res., 115, F01002, doi:10.1029/2009JF001254, 2010.

Passalacqua, P., P. Tarolli, and E. Foufoula-Georgiou, Testing space-scale methodologies for automatic geomorphic feature extraction from lidar in a complex mountainous landscape, Water Resour. Res., in press, 2010.

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This material is based upon work supported by the National Science Foundation under Grant No. 0835789. 

Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.