DEM generalization based on analysis of geometry and landscape context

Since different applications have different requests, an already generated DEM does not always suit all the demands of an application. The objective of DEM generalization is the generation of a smooth surface with a lower resolution than the original data, which should preserve topographic features and be appropriate for a smaller scale relief presentation. In this paper, a method of DEM generalization based on analysis of local geometry and landscape context is proposed. Through three kinds of filtering: low-pass filter, threshold-area-based filter and smoothing filter, the approach get four steps to generalize the DEM with lower resolution by an iterative (hierarchical) procedure. In this procedure, analysis of the fundamental landforms is based on a combination of slope gradient and curvature. A case study is put forward to give the detail explanation. Meantime, its reliability is described from elevation range and contours derived from generalized DEMs.

[1]  Jochen Schmidt,et al.  Comparison of polynomial models for land surface curvature calculation , 2003, Int. J. Geogr. Inf. Sci..

[2]  P. Pizor.  Principles of Geographical Information Systems for Land Resources Assessment. , 1987 .

[3]  Ian D. Moore,et al.  Terrain attributes: estimation methods and scale effects , 1993 .

[4]  R. J. Pike,et al.  Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature , 2007 .

[5]  Gyozo Jordan.  Adaptive smoothing of valleys in DEMs using TIN interpolation from ridgeline elevations: An application to morphotectonic aspect analysis , 2007, Comput. Geosci..

[6]  Ole Wendroth,et al.  Optimisation of relief classification for different levels of generalisation , 2006 .

[7]  A. Veldkamp,et al.  Advances in landscape - scale soil research , 2006 .

[8]  Norbert Pfeifer,et al.  Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain☆ , 2007 .

[9]  I. Evans.  Statistical Characterization of Altitude Matrices by Computer. Report 6. An Integrated System of Terrain Analysis and Slope Mapping. , 1979 .

[10]  P. A. Shary,et al.  Fundamental quantitative methods of land surface analysis , 2002 .

[11]  Steven E. Franklin,et al.  An automated approach to the classification of the slope units using digital data , 1998 .

[12]  Gyozo Jordan,et al.  Morphometric analysis and tectonic interpretation of digital terrain data: a case study , 2003 .

[13]  M. Hutchinson.  A new procedure for gridding elevation and stream line data with automatic removal of spurious pits , 1989 .

[14]  Dan Pennock,et al.  Terrain attributes, landform segmentation, and soil redistribution , 2003 .

[15]  Jochen Schmidt,et al.  Fuzzy land element classification from DTMs based on geometry and terrain position , 2004 .

[16]  B. Lowery,et al.  Identification of the spatial distribution of soils using a process-based terrain characterization , 2001 .

[17]  T. Blaschke,et al.  Automated classification of landform elements using object-based image analysis , 2006 .