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.
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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
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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
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DOI: https://doi.org/10.1007/978-1-4020-4385-7_10
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