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

Demetre, A; Angelos, T

dc.contributor.author	Demetre, A	en
dc.contributor.author	Angelos, T	en
dc.date.accessioned	2014-03-01T02:49:13Z
dc.date.available	2014-03-01T02:49:13Z
dc.date.issued	2002	en
dc.identifier.issn	0277786X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34425
dc.subject	Basin and range	en
dc.subject	Fuzzy logic	en
dc.subject	GTOPO30	en
dc.subject	Landforms	en
dc.subject	Object-oriented knowledge base	en
dc.subject	Physiographic regions	en
dc.subject	Remote sensing	en
dc.subject	Terrain analysis	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Geomorphology	en
dc.subject.other	Knowledge based systems	en
dc.subject.other	Landforms	en
dc.subject.other	Object oriented programming	en
dc.subject.other	Remote sensing	en
dc.subject.other	Digital elevation model	en
dc.subject.other	Fuzzy knowledge-based classification	en
dc.subject.other	Geomorphological mapping	en
dc.subject.other	Physiographic regions	en
dc.subject.other	Terrain analysis	en
dc.subject.other	Feature extraction	en
dc.title	Geomorphological feature extraction from a digital elevation model through fuzzy knowledge-based classification	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1117/12.463279	en
heal.identifier.secondary	http://dx.doi.org/10.1117/12.463279	en
heal.publicationDate	2002	en
heal.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.	en
heal.journalName	Proceedings of SPIE - The International Society for Optical Engineering	en
dc.identifier.doi	10.1117/12.463279	en
dc.identifier.volume	4886	en
dc.identifier.spage	516	en
dc.identifier.epage	527	en