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Object-based feature extraction using high spatial resolution satellite data of urban areas

Taubenböck, Hannes and Esch, Thomas and Wurm, Michael and Roth, Achim and Dech, Stefan (2010) Object-based feature extraction using high spatial resolution satellite data of urban areas. Journal of Spatial Science, 55 (1), pp. 117-132. Taylor & Francis.

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Abstract

Urban morphology is characterized by a complex and variable coexistence of diverse, spatially and spectrally heterogeneous objects. Built-up areas are among the most rapidly changing and expanding elements of the landscape. Thus, remote sensing becomes an essential field for up-to-date and area-wide data acquisition, especially in explosively sprawling cities of developing countries. The urban heterogeneity requires high spatial resolution image data for an accurate geometric differentiation of the small-scale physical features. This study proposes an object-based, multi-level, hierarchical classification framework combining shape, spectral, hierarchical and contextual information for the extraction of urban features. The particular focus is on high class accuracies and stable transferability by fast and easy adjustments on varying urban structures or sensor characteristics. The framework is based on a modular concept following a chronological workflow from a bottom-up segmentation optimization to a hierarchical, fuzzy-based decision fusion top-down classification. The workflow has been developed on IKONOS data for the megacity Istanbul, Turkey. Transferability is tested based on Quickbird data from the various urban structures of the incipient megacity Hyderabad, India. The validation of both land-cover classifications shows an overall accuracy of more than 81 percent.

Item URL in elib:https://elib.dlr.de/64753/
Document Type:Article
Title:Object-based feature extraction using high spatial resolution satellite data of urban areas
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Taubenböck, Hanneshannes.taubenboeck (at) dlr.deUNSPECIFIED
Esch, ThomasThomas.Esch (at) dlr.deUNSPECIFIED
Wurm, Michaelmichael.wurm (at) dlr.deUNSPECIFIED
Roth, AchimAchim.Roth (at) dlr.deUNSPECIFIED
Dech, Stefanstefan.dech (at) dlr.deUNSPECIFIED
Date:June 2010
Journal or Publication Title:Journal of Spatial Science
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:55
Page Range:pp. 117-132
Publisher:Taylor & Francis
Status:Published
Keywords:urban remote sensing; object-based classification; multi-level structure detection; fuzzy logic; decision fusion; transferability
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Taubenböck, Dr. Hannes
Deposited On:16 Sep 2010 12:33
Last Modified:06 Sep 2019 15:20

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