Geomorphological feature extraction from a digital elevation model through fuzzy knowledge-based classification

Demetre P. Argialas; Angelos Tzotsos

doi:10.1117/12.463279

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14 March 2003 Geomorphological feature extraction from a digital elevation model through fuzzy knowledge-based classification

Demetre P. Argialas, Angelos Tzotsos

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Proceedings Volume 4886, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II; (2003) https://doi.org/10.1117/12.463279
Event: International Symposium on Remote Sensing, 2002, Crete, Greece

Abstract

The objective of this research was the investigation of advanced image analysis methods for geomorphological mapping. Methods employed included multiresolution segmentation of the Digital Elevation Model (DEM) GTOPO30 and fuzzy knowledge based classification of the segmented DEM into three geomorphological classes: mountain ranges, piedmonts and basins. The study area was a segment of the Basin and Range Physiographic Province in Nevada, USA. The implementation was made in eCognition. In particular, the segmentation of GTOPO30 resulted into primitive objects. The knowledge-based classification of the primitive objects based on their elevation and shape parameters, resulted in the extraction of the geomorphological features. The resulted boundaries in comparison to those by previous studies were found satisfactory. It is concluded that geomorphological feature extraction can be carried out through fuzzy knowledge based classification as implemented in eCognition.

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Demetre P. Argialas and Angelos Tzotsos "Geomorphological feature extraction from a digital elevation model through fuzzy knowledge-based classification", Proc. SPIE 4886, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II, (14 March 2003); https://doi.org/10.1117/12.463279

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