Landform Classification in Raster Geo-images
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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