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Original Articles

A comparison of object-based and contextual pixel-based classifications using high and medium spatial resolution images

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Pages 998-1007 | Received 04 Dec 2012, Accepted 18 Jul 2013, Published online: 20 Aug 2013

References

  • 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 Salzburg 2000, Karlsruhe (Salzburg: Herbert Wichmann Verlag), pp. 12–23.
  • Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I. and Heynen, M., 2004, Multiresolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58, pp. 239–258.
  • Besag, J., 1986, On the statistical analysis of dirty pictures. Journal of the Royal Statistical Society Series B-Methodological, 48, pp. 259–302.
  • Blaschke, T., 2010, Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65, pp. 2–16.
  • Boucher, A., Seto, K.C. and Journel, A.G., 2006, A novel method for mapping land cover changes: incorporating time and space with geostatistics. IEEE Transactions on Geoscience and Remote Sensing, 44, pp. 3427–3435.
  • Chang, C.-C. and Lin, C.-J., 2011, LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2, pp. 1–27.
  • Chubey, M.S., Franklin, S.E. and Wulder, M.A., 2006, Object-based analysis of Ikonos-2 imagery for extraction of forest inventory parameters. Photogrammetric Engineering and Remote Sensing, 72, pp. 383–394.
  • Cleve, C., Kelly, M., Kearns, F.R. and Morltz, M., 2008, Classification of the wildland-urban interface: a comparison of pixel- and object-based classifications using high-resolution aerial photography. Computers Environment and Urban Systems, 32, pp. 317–326.
  • Gao, Y., Mas, J.F., Maathuis, B.H.P., Zhang, X.M. and Van Dijk, P.M., 2006, Comparison of pixel-based and object-oriented image classification approaches – a case study in a coal fire area, Wuda, Inner Mongolia, China. International Journal of Remote Sensing, 27, pp. 4039–4055.
  • Gong, P. and Howarth, P.J., 1989, Performance analyses of probabilistic relaxation methods for land-cover classification. Remote Sensing of Environment, 30, pp. 33–42.
  • Hammersley, J. and Clifford, P., 1971, Markov fields on finite graphs and lattices. Unpublished manuscript, Oxford University.
  • Huang, C., Davis, L.S. and Townshend, J.R.G., 2002, An assessment of support vector machines for land cover classification. International Journal of Remote Sensing, 23, pp. 725–749.
  • Laliberte, A.S., Rango, A., Havstad, K.M., Paris, J.F., Beck, R.F., McNeely, R. and Gonzalez, A.L., 2004, Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico. Remote Sensing of Environment, 93, pp. 198–210.
  • Landgrebe, D.A. (Ed.), 2003, Signal Theory Methods in Multispectral Remote Sensing (Hoboken, NJ: Wiley).
  • Li, S.Z. (Ed.), 2009, Markov Random Field Modeling in Image Analysis (London: Springer).
  • Liu, D. and Cai, S., 2012, A spatial-temporal modeling approach to reconstructing land-cover change trajectories from multi-temporal satellite imagery. Annals of the Association of American Geographers, 102, pp. 1329–1347.
  • Liu, D., Kelly, M. and Gong, P., 2006, A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery. Remote Sensing of Environment, 101, pp. 167–180.
  • Liu, D. and Xia, F., 2010, Assessing object-based classification: advantages and limitations. Remote Sensing Letters, 1, pp. 187–194.
  • Lu, D. and Weng, Q., 2007, A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28, pp. 823–870.
  • Lu, D.S., Hetrick, S. and Moran, E., 2011, Impervious surface mapping with Quickbird imagery. International Journal of Remote Sensing, 32, pp. 2519–2533.
  • Melgani, F. and Serpico, S.B., 2003, A Markov random field approach to spatio-temporal contextual image classification. IEEE Transactions on Geoscience and Remote Sensing, 41, pp. 2478–2487.
  • Newman, M.E., McLaren, K.P. and Wilson, B.S., 2011, Comparing the effects of classification techniques on landscape-level assessments: pixel-based versus object-based classification. International Journal of Remote Sensing, 32, pp. 4055–4073.
  • Persello, C. and Bruzzone, L., 2010, A novel protocol for accuracy assessment in classification of very high resolution images. IEEE Transactions on Geoscience and Remote Sensing, 48, pp. 1232–1244.
  • Platt, R.V. and Rapoza, L., 2008, An evaluation of an object-oriented paradigm for land use/land cover classification. Professional Geographer, 60, pp. 87–100.
  • Pontius, R.G. and Millones, M., 2011, Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing, 32, pp. 4407–4429.
  • Robertson, L.D. and King, D.J., 2011, Comparison of pixel- and object-based classification in land cover change mapping. International Journal of Remote Sensing, 32, pp. 1505–1529.
  • Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M. and Schirokauer, D., 2006, Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogrammetric Engineering and Remote Sensing, 72, pp. 799–811.

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