Landform Classification in Raster Geo-images

  • Marco Moreno
  • Serguei Levachkine
  • Miguel Torres
  • Rolando Quintero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)


We present an approach to perform a landform classification of raster geo-images to obtain the semantics of DEMs. We consider the following raster layers: slope, profile curvature and plan curvature, which have been built to identify the intrinsic properties of the landscape. We use a multi-valued raster to integrate these layers. The attributes of the multi-valued raster are classified to identify the landform elements. The classification approach is used to find the terrain characteristics of the water movement. Moreover, we describe the mechanisms to compute the primary attributes of digital terrain model. The method has been implemented into Geographical Information System–ArcInfo, and applied for Tamaulipas State, Mexico.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Marco Moreno
    • 1
  • Serguei Levachkine
    • 1
  • Miguel Torres
    • 1
  • Rolando Quintero
    • 1
  1. 1.Geoprocessing Laboratory-Centre for Computing Research-National Polytechnic InstituteMexico CityMexico

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