Adaptive Smoothing for Noisy DEMs

Geomorphometry 2011Geomorphometry 2011, 07-09 September 2011, Esri, Redlands, California

John Gallant

“DEMs derived from dense remotely sensed measurements, including lidar- and radar-based DEMs, provide much greater surface detail than traditional interpolated DEMs but suffer from random noise that perturbs measures of surface shape such as slope and flow direction. Smoothing is an effective method of reducing noise but also tends to impact on important surface features, lowering hilltops, raising valleys and obliterating important fine detail.

Shaded relief of a sub-section of the area in Figures 1 and 3 from SRTM data before (left) and after (right) adaptive smoothing.

Shaded relief of a sub-section of the area in Figures 1 and 3 from SRTM data before (left) and after (right) adaptive smoothing.

“This paper describes a multiscale adaptives moothing approach that responds to both the relief and noise level in a DEM by smoothing aggressively where the noise is larger than the local relief and smoothing little or not at all where noise is less than relief. The method is simple and efficient and can be readily implemented in a raster GIS environment. The method is demonstrated on noisy SRTM data”

All presentation materials and reviewed papers from Geomorphometry 2011 are available at http://geomorphometry.org/content/geomorphometry-2011-programme.

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