GI_Forum 2013, Volume 1 Creating the GISociety – Conference Proceedings
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2013, Volume 1 Creating the GISociety – Conference Proceedings
ISSN 2308-1708 Online Edition ISBN 978-3-87907-532-4 Print Edition ISBN 978-3-7001-7438-7 Online Edition
doi:10.1553/giscience2013
GI_Forum, Volume 1 2013, 566 pages Print edition is available at Wichmann-Verlag, Berlin
Josef Hecher,
Anthony Filippi,
Inci Guneralp,
Gernot Paulus
S. 187 - 196 doi:10.1553/giscience2013s187 Verlag der Österreichischen Akademie der Wissenschaften
Abstract: Automatic feature extraction from satellite imagery is cost effective and fast. An essential issue in this context is the degree of accuracy for thematic correctness obtainable through common pixel-based and object-oriented classification algorithms. By applying two classification algorithms to Landsat 5 TM imagery for the extraction of different morphological river features the thematic correctness of the resulting raster images and the separability of the river features is evaluated. River features of meandering rivers evolve through dynamic avulsion, erosion and deposition processes. Although many studies focus on the analysis of these river environments, diverse methods of GIS and remote sensing based river feature classification methods have not been evaluated and assessed yet. In the literature several techniques to monitor spatio-temporal changes such as lateral river channel migration are already mentioned but the tendency there is to identify the changes by examining time spans rather than a point in time. Besides that the semiautomatic river feature methods described in related studies mainly focus on the identification of a river channel itself and do not consider additional features such as oxbows, scars, relic channels, etc. that in fact are significant characters in riverine environments. Therefore, this paper evaluates the application of a supervised classification using ENVI’s Support Vector Machine and an object based classification using the ArcGIS extension Feature Analyst to extract river features from Landsat 5 TM images including ancillary data files. Furthermore, the results of the classification methods are evaluated with regard to thematic correctness and separability of the various classified river features using accuracy assessment as presented in the specialist literature. Finally the long-time changes in the riverine environments are traced by interpreting the distribution of the classified river features. Accordingly, the approach of this work contributes to on-going research concerning semiautomatic or automatic river feature extraction. Published Online: 2013/06/20 17:39:39 Object Identifier: 0xc1aa5576 0x002e6e60 Rights:https://creativecommons.org/licenses/by-nd/4.0/
GIS as a technology has come a long way, from the
early adoption of technical wizardry to the ubiquitous,
if unconscious use by the masses. The creation
of the GISociety is on its way through technological
development, theoretical and empirical scientific
research and inclusion of technology into education
with increasing pedagogical justification.
Defining new dimensions of hard- and software,
brainware and orgware are all needed to further
develop the GISociety.
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |