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Object-oriented classification of alpine landforms from an ASTER scene and digital elevation data (Reintal, Bavarian Alps)


Schneevoigt, N J; van der Linden, S; Kellenberger, Tobias; Kääb, Andreas; Schrott, L (2010). Object-oriented classification of alpine landforms from an ASTER scene and digital elevation data (Reintal, Bavarian Alps). In: Kaufmann, Viktor; Sulzer, Wolfgang. Proceedings of the 10th International Symposium on High Mountain Remote Sensing Cartography held in Kathmandu, Nepal 8-11 September 2008. Graz: Institute of Geography and Regional Science, Karl-Franzens University of Graz, 53-62.

Abstract

High mountain regions represent difficult terrain for detecting rock and sediment storage areas. By means of a satellite scene by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and a digital elevation model, the geomorphological setting of the Reintal subcatchment (17 km2) east of the Zugspitze is analysed. Characteristic landforms are classified in an object-oriented approach comprising four spatial levels of differentiation. The complex, object-based decision tree hierarchy largely founds on fuzzy membership functions and to a lesser extent on a minimum distance classifier. The final landform classification scores high in the accuracy assessments. The results show that an identification of the present-day pattern of geomorphological process units is possible by remote sensing. Besides, the approach provides a first insight into the otherwise inaccessible upper regions of the study area which could not be included in any previous survey.

Abstract

High mountain regions represent difficult terrain for detecting rock and sediment storage areas. By means of a satellite scene by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and a digital elevation model, the geomorphological setting of the Reintal subcatchment (17 km2) east of the Zugspitze is analysed. Characteristic landforms are classified in an object-oriented approach comprising four spatial levels of differentiation. The complex, object-based decision tree hierarchy largely founds on fuzzy membership functions and to a lesser extent on a minimum distance classifier. The final landform classification scores high in the accuracy assessments. The results show that an identification of the present-day pattern of geomorphological process units is possible by remote sensing. Besides, the approach provides a first insight into the otherwise inaccessible upper regions of the study area which could not be included in any previous survey.

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Item Type:Book Section, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2010
Deposited On:16 Apr 2013 09:04
Last Modified:05 Apr 2016 16:44
Publisher:Institute of Geography and Regional Science, Karl-Franzens University of Graz
Series Name:Grazer Schriften der Geographie und Raumforschung
Number:45
ISBN:978-3-9502276-5-9
Free access at:Official URL. An embargo period may apply.
Official URL:http://www.uni-graz.at/geowww/hmrsc/hmrsc-x/HMRSC-X_all.pdf

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