Geomorphometry

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Geomorphometry in GRASS

Geomorphometry is viewed as the science of quantitative analysis of earth surface shape (Pike, 2000).

An usual workflow in Geomorphometry is broken in three main sections: input, analysis and output (Hengl and Evans, 2009). Input operations refer to the import of altitude data or DEMs, or to DEM generation. Analysis operations refer to the preprocessing of DEMs for extraction of geomorphometric variables and geomorphometric objects. Output operations refer to the use of geomorphometric data for various applications.

Import of DEMs

  • Grid-based DEMs in various formats can be imported using the r.in.gdal command.

Import of elevation data

  • Elevation data represented by digitized contours or measured points can be imported using the v.in.ogr command that supports numerous vector formats
  • Data given as an ASCII list of (x, y, z) coordinates can be imported with v.in.ascii
  • Very dense ASCII point data (e.g. from LiDAR), can be directly converted to raster using r.in.xyz by performing a binning procedure based on different statistical measures (min, max, mean, range, etc.).

Generation of DEMs

  • Elevation data used in DEM generation represent an sampling of elevations from a certain surface. This discrete data need to be transformed into a continuous representation by using interpolators.
  • Interpolation of DEMs from elevation data functions can be called from Raster / Interpolate Surfaces

Preprocessing of DEMs

  • DEMs generated from elevation data often contains errors or have a model of representation which is not suitable for a certain applications, so some operation are needed for obtaining a valid DEM.

Deriving geomorphometric variables

Deriving objects variables

Useful commands

References

  • Grohmann, C.H., 2004. Morphometric analysis in geographic information systems: applications of free software GRASS and R. Computers & Geosciences, 30(9-10), pp.1055-1067. http://dx.doi.org/10.1016/j.cageo.2004.08.002
  • Grohmann, C.H., 2005. Trend-surfaces analysis of morphometric parameters: A case study in southeastern Brazil Computers & Geosciences, 31, 1005-1014. http://dx.doi.org/10.1016/j.cageo.2005.02.011
  • Grohmann, C. H.; Riccomini, C. & Alves, F. M. , 2007. SRTM-based morphotectonic analysis of the Pocos de Caldas Alkaline Massif, southeastern Brazil Computers & Geosciences, 33, 10-19. http://dx.doi.org/10.1016/j.cageo.2006.05.002
  • Grohmann, C. H. & Riccomini, C., 2009. Comparison of roving-window and search-window techniques for characterising landscape morphometry Computers & Geosciences, 35, 2164-2169. http://dx.doi.org/10.1016/j.cageo.2008.12.014
  • Grohmann, C. H.; Smith, M. J. & Riccomini, C., 2010. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland Geoscience and Remote Sensing, IEEE Transactions on, 49, 1200-1213. http://dx.doi.org/10.1109/TGRS.2010.2053546
  • Grohmann, C. H.; Riccomini, C. & Chamani, M. A. C., 2011. Regional scale analysis of landform configuration with base-level (isobase) maps Hydrology and Earth System Sciences, 15, 1493-1504. http://dx.doi.org/10.5194/hess-15-1493-2011
  • Hengl, T. & Reuter, H.I., 2009. Geomorphometry: concepts, software, applications, Amsterdam; Oxford: Elsevier. http://geomorphometry.org/book
  • Hofierka, J., Mitasova, H. & Neteler, M., 2009. Geomorphometry in GRASS GIS. In Developments in Soil Science. Elsevier, pp. 387-410. Available at: http://dx.doi.org/10.1016/S0166-2481(08)00017-2.
  • Le Coz, M. et al., 2009. Assessment of Digital Elevation Model (DEM) aggregation methods for hydrological modeling: Lake Chad basin, Africa. Computers & Geosciences, 35(8), pp.1661-1670.
  • Pike, Richard J., 2000.Geomorphometry - diversity in quantitative surface analysis, Progress in Physical Geography, 1-20.