Landform classification in raster geo-images

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6 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditoresAlberto Sanfeliu, Jose Francisco Martinez-Trinidad, Jesus Ariel Carrasco-Ochoa
EditorialSpringer Verlag
Páginas558-565
Número de páginas8
ISBN (versión impresa)3540235272
DOI
EstadoPublicada - 2004

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen3287
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

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