@inproceedings{fdb3ef6bc03f45b494e4087a9e061d90,
title = "Automatic geomorphometric analysis for digital elevation models",
abstract = "We present an approach to perform geomorphometric analysis for Digital Elevation Models (DEM) to obtain the Cartographic Knowledge Domain (CKD) of the landscapes. CKD is oriented to represent the essential properties of DEM by means of concepts. These properties are obtained by analyzing the terrain topography. This analysis is based on two classifications: landform and topographic ruggedness. The approach involves the following raster layers: slope, profile curvature and plan curvature (primary attributes), which have been built to identify the intrinsic properties of the landscape. We use a multi-valued raster to integrate the primary attributes of DEM to generate the landform classification layer in order to find the terrain characteristics of the water movement. The topographic ruggedness is used to express the amount of elevation difference between adjacent cells of DEM. The topographic ruggedness is presented by means of Terrain Ruggedness Index (TRI). This work is oriented to support subsequent processes. The method has been implemented into Geographical Information System - ArcInfo, and applied for Tamaulipas State, Mexico.",
author = "Miguel Moreno and Serguei Levachkine and Miguel Torres and Rolando Quintero and G. Guzman",
year = "2005",
doi = "10.1007/11554028_52",
language = "Ingl{\'e}s",
isbn = "354028897X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "374--381",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings",
address = "Alemania",
note = "9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 ; Conference date: 14-09-2005 Through 16-09-2005",
}