Terrain Generalisation

Contour Lines Generation in Karstic Plateaus for Topographic Maps

“…the sinkholes, our objectives is very close to a map generalisation problem, and it seems relevant to look at the literature on relief.contour lines generalisation. Guilbert et al (2014) give a nice overview of these terrain generalisation techniques. Once again, there is clear focus on the classification of landforms to adapt the generalisation operations to these landforms: for instance, Guilbert (2013) identifies the key landforms to derive multi-scale bathymetric contours.…”

A high-fidelity multiresolution DEM model for Earth systems

“…Systematic scale transformation of topographic data has long been studied under terrain generalisation, where precise surface approximation and terrain structural feature retention have both been pursued (Ai and Li, 2010;Chen et al, 2015;Guilbert et al, 2014;Jenny et al, 2011;Weibel, 1992;Zhou and Chen, 2011). Triangulated irregular networks (TIN) are generally chosen as a substitute for the regularly spaced grids (RSG), and terrain feature points (critical points or salient points from some significance metric) are selected for constructing the network.…”

“…Critical points or salient points are selected because they can effectively improve the approximation precision (Heckbert and Garland, 1997;Zakšek and Podobnikar, 2005;Zhou and Chen, 2011). As surface approximation precision and terrain feature retention are competitive for the redistribution of feature points, DEM (digital elevation model) generalisation is differentiated from terrain generalisation by its emphasis on surface approximation as a whole, with the aim of providing precise surface interpolation (Guilbert et al, 2014). Terrain generalisation emphasises geomorphology or landform depiction, where map generalisation measures (such as abstracting, smoothing) are drawn to produce progressive data reduction, with the effect that the main relief features are strongly stressed while non-structural details are massively suppressed (Ai and Li, 2010;Guilbert et al, 2014;Jenny et al, 2011).…”

“…As surface approximation precision and terrain feature retention are competitive for the redistribution of feature points, DEM (digital elevation model) generalisation is differentiated from terrain generalisation by its emphasis on surface approximation as a whole, with the aim of providing precise surface interpolation (Guilbert et al, 2014). Terrain generalisation emphasises geomorphology or landform depiction, where map generalisation measures (such as abstracting, smoothing) are drawn to produce progressive data reduction, with the effect that the main relief features are strongly stressed while non-structural details are massively suppressed (Ai and Li, 2010;Guilbert et al, 2014;Jenny et al, 2011). Since the static topographic layers are commonly composed directly from DEM datasets for diverse simulation interests, maintaining precise surface approximation for rigorous boundary conditions is often more important than 'sparse' geomorphology representation.…”

“…Terrain surface critical points such as peaks, pits, and saddles are treated as gravity equilibria and key elements depicting the surface geometry in the large (Banchoff, 1967;Milnor, 1963); a further extension of the critical points on a secondorder surface derivatives will describe a more fundamental terrain geometry shape (Jenny et al, 2011;Kennelly, 2008). When constructing a generalised DEM surface, these feature points are commonly used as a base set, and additional input points, or pre-extracted terrain structures are embedded for further approximation (Guilbert et al, 2014;Zakšek and Podobnikar, 2005;Zhou and Chen, 2011). The additional input points or pre-extracted terrain structures of interest are also commonly required in numerical simulation setups for cross-checking or validation purposes.…”