Abstract
This chapter focuses on segmentation of remotely sensed image data and object-based image analysis. It discusses the differences between pixel-based and object-based image analysis; the potential of the object-based approach; and, the application of eCognition software for performing image segmentation and classification at different levels of detail.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Antunes AF, Lingnau C, Da Silva JC (2003) Object oriented analysis and semantic network for high resolution image classification. In: Proceedings of Anais XI SBSR Conference, Belo Horizonte, Brazil, 05–10 Apr 2003, INPE, pp 273–279
Baatz M, Schäpe A (1999) Object-oriented and multi-scale image analysis in semantic networks. In: Proceedings of the 2nd international symposium on operationalization of remote sensing, Enschede, ITC, 16–20 Aug 1999
Binnig G, Baatz M, Klenk J, Schmidt G (2002) Will machines start to think like humans? Europhy News 33(2). Online http://www.europhysicsnews.com/full/14/article2/article2.html. Accessed Sept 2005
Blaschke T, Strobl J (2001) What`s wrong with pixels? Some recent developments interfacing remote sensing and GIS. GIS Zeitschrift für Geoinformationssysteme 6:12–17
Congalton RG, Green K (1998) Assessing accuracy remotely sensed data principles practices. Mapping science series. CRC Press, London
Darwish A, Leukert K, Reinhardt W (2003) Urban land-cover classification: an object based perspective. In: Proceedings of the 2nd GRSS/ISPRS Joint Workshop on Data Fusion and remote sensing over urban areas. URBAN 2003, Berlin, pp 277–282
De Kok R, Wever T, Flockelmann R (2003) Analysis of urban structure and development applying procedures for automatic mapping of large area data. In: Juergens, C (ed) Remote sensing of urban areas. In: Proceedings of the 4th international symposium held in Regensburg/Germany, 27–29 June 2003. (The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXIV–7/W9) (CD-ROM): 41–46
eCognition User Guide (2004) Munich, Germany. http://www.definiens-imaging.com. Accessed 20 Feb 2009
Erdas Imagine®/Leica-Geosystems, Image Segmentation (2004) http://www2.erdas.com/supportsite/downloads/tools/descriptions/tool_descriptions.html#image_seg. Accessed 20 Feb 2009
Hay GJ, Blaschke T, Marceau DJ, Bouchard A (2003) A comparison of three image–object methods for the multiscale analysis of landscape structure. Photogramm Remote Sens 57:327–345
Hofmann P (2001) Detecting informal settlements from IKONOS image data using methods of object oriented image analysis – an example from Cape Town (South Africa). In: Juergens C (ed) Remote sensing of urban areas – Fernerkundung in urbanen Räumen. In: Proceedings (Abstracts and Full papers on Supplement CD-ROM) of the 2nd international symposium held in Regensburg/Germany, 22–23 June 2001-Regensburger Geographische Schriften 35, Regensburg
Koch B, Jochum M, Ivits E, Dees M (2003) Pixelbasierte Klassifizierung im Vergleich und zur Ergänzung zum objektbasierten Verfahren. Photogrammetrie Fernerkundung Geoinformation 3(2003):195–204
Lang S, Schöpfer E, Blaschke T (2003) Object-specifc change detection based on assisted feature extraction: a case study of an expanding suburban area. In: Juergens C (ed) Remote sensing of urban areas. In: Proceedings of the 4th international symposium held in Regensburg/Germany, 27–29 June 2003. (The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXIV-7/W9) (CD-ROM): 93–98
Neubert M, Meinel G (2003) Evaluation of segmentation programs for high resolution remote sensing applications. In: Schroeder M, Jacobsen K, Heipke C (eds) In: Proceedings of the Joint ISPRS/EARSeL Workshop “High Resolution Mapping from Space 2003”, Hannover, Germany, 6–8 Oct 2003 (published on CD only)
Pinz A (1994) Bildverstehen. Springer, Vienna (in German)
Tadesse W, Coleman TL, Tsegaye TD (2003) Improvement of land use and land cover classification of an urban area using image segmentation from Landsat ETM+ data. In: Proceedings of the 30th international symposium on remote sensing of the environment, 10–14 Nov 2003, Honolulu, Hawaii
Visual Learning Systems, Feature Analyst (2004) http://www.featureanalyst.com/. Accessed 20 Feb 2009
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Netherlands
About this chapter
Cite this chapter
Schöpfer, E., Lang, S., Strobl, J. (2010). Segmentation and Object-Based Image Analysis. In: Rashed, T., Jürgens, C. (eds) Remote Sensing of Urban and Suburban Areas. Remote Sensing and Digital Image Processing, vol 10. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4385-7_10
Download citation
DOI: https://doi.org/10.1007/978-1-4020-4385-7_10
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-4371-0
Online ISBN: 978-1-4020-4385-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)