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

References

• Albertz , J. and Wiggenhagen , M. 2009 . Guide for Photogrammetry and Remote Sensing , Heidelberg : Wichmann .
   Google Scholar
• Arroyo , L. A. , Healey , S. P. , Cohen , W. B. , Cocero , D. and Manzanera , J. A. 2006 . Using object-oriented classification and high-resolution imagery to map fuel types in a Mediterranean region . Journal of Geophysical Research , 111 G04S04, doi:10.1029/2005JG000120
   PubMed Web of Science ®Google Scholar
• Baatz , M. and Schäpe , A. 2000 . “ Multiresolution segmentation – an optimization approach for high quality multi-scale image segmentation ” . In Angewandte geographische Informationsverarbeitung XII: Beiträge zum AGIT-Symposium 12 – 23 . Salzburg
   Google Scholar
• Batty , M. and Howes , D. 2001 . “ Predicting temporal patterns in urban development from remote sensing ” . In Remote Sensing and Urban Analysis , Edited by: Donnay , J. , Barnsley , M. and Longley , P. 185 – 204 . London : Taylor and Francis .
   Google Scholar
• Bauer , T. and Steinnocher , K. 2001 . Per parcel land use classification in urban areas applying a rule-based technique . GeoBIT/GIS , 6 : 24 – 27 .
   Google Scholar
• Barr , S. L. , Barnsley , M. J. and Steel , A. 2004 . On the separability of urban land-use categories in fine spatial scale land-cover data using structural pattern recognition . Environment and Planning B: Planing and Design , 32 : 397 – 418 .
   Google Scholar
• Benediktson , J. A. , Pesaresi , M. and Arnason , K. 2003 . Classification and feature extraction for remote sensing images from urban areas based on morphological transformations . IEEE Transactions on Geoscience and Remote Sensing , 41 ( 9 ) : 1940 – 1949 .
   Web of Science ®Google Scholar
• Benz , U. , Hofmann , P. , Willhauck , G. , Lingenfelder , I. and Heynen , M. 2004 . Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information . ISPRS Journal of Photogrammetry & Remote Sensing , 58 : 239 – 258 .
   Web of Science ®Google Scholar
• Blaschke , T. , Lang , S. , Lorup , E. , Strobl , J. and Zeil , P. 2000 . “ Object-oriented image processing in an integrated GIS/remote sensing environment and perspectives for environmental applications ” . In Environmental Information for Planning, Politics and the Public , Edited by: Cremers , A. and Greve , K. Marburg : Metropolis .
   Google Scholar
• Brunn , S. , Zeiger , D. and Williams , J. 2003 . Cities of the World – World Regional Urban Development , 568 New York : Rowman & Littlefield .
   Google Scholar
• Bruzzone , L. and Carlin , L. 2006 . A multilevel context-based system for classification of very high spatial resolution images . IEEE Transactions on Geoscience and Remote Sensing , 44 ( 9 ) : 2587 – 2600 .
   Web of Science ®Google Scholar
• Clinton , N. , Holt , A. , Yan , L. and Gong , P. July 2008 . “ An accuracy assessment measure for object based image segmentation ” . In XXIth ISPRS Congress , Vol. XXXVII , July , Beijing, , China : IAPRS .
   Google Scholar
• De Martinao , M. , Causa , F. and Serpico , S. B. July 2003 . “ Classification of optical high resolution images in urban environment using spectral and textural information ” . In Proc. IGARSS Vol. 1 , July , 467 – 469 .
   Google Scholar
• Donnay , J. , Barnsley , M. and Longley , P. 2000 . Remote Sensing and Urban Analysis , London : Taylor and Francis .
   Google Scholar
• Esch , T. 2006 . “ Automatisierte Analyse von Siedlungsflächen auf der Basis höchstauflösender Radardaten ” . PhD Thesis. Bayerische Julius-Maximilian Universität
   Google Scholar
• Esch , T. , Roth , A. and Dech , S. Robust approach towards an automated detection of built-up areas from high resolution radar imagery . Proceedings of the ISPRS WG VII/1 Human Settlements and Impact Analysis, 3rd International Symposium Remote Sensing and Data Fusion Over Urban Areas (URBAN 2005) and 5th International Symposium Remote Sensing of Urban Areas (URS 2005) . March 14–16 .
   Google Scholar
• Esch , T. , Thiel , M. , Bock , M. and Dech , S. 2008 . Improvement of image segmentation accuracy based on multi-scale optimization procedure . IEEE Geoscience and Remote Sensing Letters , 5 ( 3 )
   Web of Science ®Google Scholar
• Fauvel , M. , Chanussot , J. and Benediktsson , J. A. 2006 . Decision fusion for the classification of urban remote sensing images . IEEE Transactions on Geoscience and Remote Sensing , 44 ( 10 ) : 2828 – 2837 .
   Web of Science ®Google Scholar
• Foody , G. M. 1996 . Approaches for the production and evaluation of fuzzy land-cover classification from remotely-sensed data . International Journal of Remote Sensing , 17 : 1317 – 1340 .
   Web of Science ®Google Scholar
• Gamba , P. , Dell' Acqua , F. , Lisini , G. and Trianni , G. 2007 . Improved VHR Urban Area Mapping Exploiting Object Boundaries . IEEE Transactions on Geoscience and Remote Sensing , 45 ( 8 ) : 2676 – 2682 .
   Web of Science ®Google Scholar
• Haralick , R. M. and Shapiro , L. G. 1985 . Image segmentation techniques . Computer Vision, Graphics and Image Processing , 29 ( 1 ) : 100 – 132 .
   Google Scholar
• Herold , M. 2002 . “ Object-oriented mapping and analysis of urban land use/cover using IKONOS data ” . In Proceedings of 22nd EARSEL Symposium ‘Geoinformation for European-wide Integration’ , Rotterdam : Millpress .
   Google Scholar
• Hofmann , P. Detecting urban features from IKONOS data using an object-oriented approach . Proceedings of the First Annual Conference of the Remote Sensing & Photogrammetry Society . September 12–14 . pp. S28 – 33 .
   Google Scholar
• Jensen , J. R. 2005 . Introductory Digital Image Processing. A Remote Sensing Perspective , Pearson Education .
   Google Scholar
• Jensen , J. R. 2007 . Remote Sensing of the Environment: An Earth Resource Perspective , Pearson Prentice Hall .
   Google Scholar
• Klir , G. J. and Yuan , B. 1995 . Fuzzy Sets and Fuzzy Logic: Theory and Application. , 1st ed. , Englewood Cliffs, NJ : Prentice Hall .
   Google Scholar
• Kux , H. J.H. and Araújo , E. H.G. 2008 . “ Object-based image analysis using QuickBird satellite images and GIS data, case study Belo Horizonte (Brazil) ” . In Object-Based Image Analysis – Spatial Concepts for Knowledge-Driven Remote Sensing Applications , Edited by: Blaschke , T. , Lang , S. and Hay , G. Berlin : Springer .
   Google Scholar
• Landgrebe , D. A. 2003 . Signal Theory Methods in Multispectral Remote Sensing , New York : Wiley .
   Google Scholar
• Lillesand , T. M. and Kiefer , R. W. 2000 . Remote Sensing and Image Interpretation , New York : John Wiley .
   Google Scholar
• Maktav , D. and Erbek , F. S. 2005 . Analysis of urban growth using multitemporal satellite data in İstanbul, Turkey . International Journal of Remote Sensing , 26 ( 4 )
   Web of Science ®Google Scholar
• Mather , P. M. 2004 . Computer Processing of Remotely-Sensed Images: An Introduction. , 3rd ed. , New York : John Wiley .
   Google Scholar
• Meher , S. K. , Shankar , B. U. and Ghosh , A. 2007 . Wavelet-feature-based classifiers for multispectral remote-sensing images . IEEE Transactions on Geoscience and Remote Sensing , 45 ( 6 ) : 1881 – 1886 .
   Web of Science ®Google Scholar
• Neubert , M. and Herold , H. 2008 . “ Assessment of remote sensing image segmentation quality ” . In GEOBIA 2008 – Pixels, Objects, Intelligence
   Google Scholar
• Schiewe , J. 2002 . “ Segmentation of high-resolution remotely sensed data – concepts, applications and problems ” . In Symposium on Geospatial Theory, Processing and Applications Ottawa
   Google Scholar
• Shackelford , A. K. and Davis , C. H. 2003 . A combined fuzzy-pixel based and object-based approach for classififcation of high resolution multi-spectral data over urban areas . IEEE Transactions on Geoscience and Remote Sensing , 41 ( 10 ) : 2354 – 2363 .
   Web of Science ®Google Scholar
• Stolz , R. 1998 . Die Verwendung der Fuzzy Logic Theorie zur wissensbasierten Klassifikatiom von Fernerkundungsdaten , Munich : Reihe B. Geobuch .
   Google Scholar
• Taubenböck , H. 2008 . “ Vulnerabilitätsabschätzung der Megacity Istanbul mit Methoden der Fernerkundung ” . PhD Thesis. University of Würzburg, p. 178, available at: http://www.opus-bayern.de/uni-wuerzburg/volltexte/2008/2804/
   Google Scholar
• Taubenböck , H. and Roth , A. 2007 . “ A transferable and stable classification approach in various urban areas and various high resolution sensors ” . In Proceedings of the Urban Remote Sensing Joint Event 7 Paris
   Google Scholar
• Taubenböck , H. , Habermeyer , M. , Roth , A. and Dech , S. 2006 . Automated allocation of highly-structured urban areas in homogeneous zones from remote sensing data by Savitzky-Golay Filtering and curve sketching . IEEE Geoscience and Remote Sensing Letters , 3 ( 4 ) : 532 – 536 .
   Web of Science ®Google Scholar
• Thomas , N. , Hendrix , C. and Congalton , R. 2003 . A comparison of urban mapping methods using high-resolution digital imagery . Photogrammetric Engineering and Remote Sensing , 69 : 963 – 972 .
   Web of Science ®Google Scholar
• Tian , J. and Chen , D. M. 2007 . Optimization in multi-scale segmentation of high resolution satellite images for artifical feature recognition . International Journal of Remote Sensing , 28 : 4625 – 4644 .
   Web of Science ®Google Scholar
• Tso , B. and Mather , P. M. 2001 . Classification Methods for Remotely Sensed Data , London : Taylor and Francis .
   Google Scholar
• United Nations . 2007 . World Urbanization Prospects, The 2007 Revision New York
   Google Scholar
• Van Der Sande , C. J. , De Jong , S. M. and De Roo , A. P.J. 2003 . A segmentation and classification approach of IKONOS-2 imagery for land-cover mapping to assist flood risk and flood damage assessment . International Journal of Applied Earth Observation and Geoinformation , 4 : S217 – 229 .
   Google Scholar
• Yager , R. 1987 . Fuzzy Sets and Applications: Selected Papers by L. Zadeh , New York : John Wiley .
   Google Scholar
• Zhou , W. and Troy , A. 2008 . An object-oriented approach for analysing and characterizing urban landscape at the parcel level . International Journal of Remote Sensing , 29 ( 11 ) : 3119 – 3135 .
   Web of Science ®Google Scholar