Digital Terrain Models by M. Varshosaz 1 DTM tasks: generation  Buy global or national data set  Collect data

Digital Terrain Models by M. Varshosaz 2 Buy global or national data set

Digital Terrain Models by M. Varshosaz 3 Examples Topographic Data (*) completed [Eidenbenz et al, 1997]

4 DTM tasks: generation  Main steps  Data capture  Data  Sampling  Choice of data source  Data acquisition techniques  Model construction  Establishment of topological relations  Defining a suitable interpolation method

5 Data  Data for a DTM should consist of:  Elevation Data:  Observations about terrain elevations.  Morphological Information:  Information about phenomena that significantly influence the shape of the terrain surface (i.e. structural features such as drainage channels, ridges and other surface discontinuities).  Key issue:  The selection of a particular data acquisition technique for any given application considering the available/required efficiency, cost, and technological maturity.

6 Sampling techniques  Choice of sampling technique  Terrain shape  Available instrumentation  Required accuracy  Techniques:  Random/Selective  Systematic/grid based  Progressive  Composite

7 Selective Sampling  Capture topographic break lines.  Advantage:  Capture all the morphological information associated with the surface.  Elevation data are collected whenever needed.  Disadvantage:  Requires experienced human operator.  Automation is very difficult.

8 Random/Selective sampling  Selection of significant points by the operator  Usually results in less points  More thought should be given to the structuring and management of the measured data  Can not be automated

9 Systematic/grid based  Systematic pattern of spot heights  Can be squares, rectangles, triangles, or hexagonal  Sampling patterns are arranged as profiles or regular geometric shapes.  Fixed sampling distance is used:  Need to determine the optimal sampling interval.

10 Grid Sampling: Discussion  Location of the required grid node is preprogrammed and driven under computer control.  Advantage:  Can easily be programmed  May be applied in a semi-automated or automatic mode.  Disadvantages:  Too many points are sampled in low relief regions.  Too few points are captured in rugged terrain.

11 Progressive Sampling: Procedure  The sampling process is initiated by measuring a low-density grid.  The accuracy of the sampled data is then analysed  Wherever necessary, the sampling grid is recursively densified until the required accuracy level is reached.

12 Progressive Sampling: Discussion  Advantage:  Fewer points are needed to accurately represent the DTMs.  Disadvantage:  Details may still be disregarded in the first run  Still more points than necessary  Too many points in terrain breaks  May fail in areas with sharp discontinuities

13 Composite Sampling  Composite Sampling = Progressive sampling / Systematic sampling + selective sampling:  Selective sampling is used to capture abrupt surface changes.  Progressive sampling yields the data for the rest of the terrain.  Advantage:  Recursive refinement of progressive sampling is kept to a minimum and terrain discontinuities are represented accurately.  Disadvantage:  Requires human intervention (partial automation).

14 Composite  Combines grid based and selective techniques  Can only partially be automated

15 Sampling Methods: Summary

16 Data capture  The choice of data source  Size of the area to be modelled  Required accuracy  Type of the data to be extracted  Cost and technological maturity

Data capture techniques  Data capture techniques  Ground surveying  Photogrammetry  Digitising cartographic data sources  RADAR, LIDAR (or Laser Scanning), and sonar. 17

18 Choice of Data Acquisition Techniques