Classification of Polarimetric SAR Data Based on Object-Based Multiple Classifiers for Urban Land-Cover

Journal of the Indian Society of Remote Sensing

Volumn 44, Issue 6, 2016, Pages 855-863

  Habibi, Masoud ^a   Sahebi, Mahmod Reza ^a   Maghsoudi, Yasser ^a   Ghayourmanesh, Shaheen ^b  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

Multiple classifier; Object based classification; PolSAR; SVM

Indexed keywords

IMAGE ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; NOISE; SEGMENTATION; SPECKLE; SUPPORT VECTOR MACHINE; SYNTHETIC APERTURE RADAR; URBAN AREA;

EID: 84960108781     PISSN: 0255660X     EISSN: 09743006     Source Type: Journal    
DOI: 10.1007/s12524-016-0558-5     Document Type: Article

References (36)

1. Barnes, R. (1988). Roll invariant decompositions for the polarization covariance matrix. In Polarimetry technology workshop, Redstone Arsenal, AL.
2. Barnes, C. F., & Burki, J. (2006). Late-season rural land-cover estimation with polarimetric-SAR intensity pixel blocks and-tree-structured near-neighbor classifiers. IEEE Transactions on Geoscience and Remote Sensing, 44(9), 2384–2392.
3. Bernard, K., Tarabalka, Y., Angulo, J., Chanussot, J., & Benediktsson, J. A. (2012). Spectral–spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach. IEEE Transactions on Image Processing, 21(4), 2008–2021.
4. Blaschke, T., & Hay, G. J. (2001). Object-oriented image analysis and scale-space: theory and methods for modeling and evaluating multiscale landscape structure. International Archives of Photogrammetry and Remote Sensing, 34(4), 22–29.
5. Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123–140.
6. Briem, G. J., Benediktsson, J. A., & Sveinsson, J. R. (2002). Multiple classifiers applied to multisource remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 40(10), 2291–2299.
7. Cameron, W. L., & Leung, L. K. (1990). Feature motivated polarization scattering matrix decomposition. In IEEE 1990 International Radar Conference (Vol. 1, pp. 549-557).
8. Cloude, S. R. (1985). Target decomposition theorems in radar scattering. Electronics Letters, 21(1), 22–24.
9. Cloude, S. R., & Pottier, E. (1997). An entropy based classification scheme for land applications of polarimetric SAR. IEEE Transactions on Geoscience and Remote Sensing, 35(1), 68–78.
10. Dong, Y., & Milne, A. K. (2001). Segmentation and classification of vegetated areas using polarimetric SAR image data. IEEE Transactions on Geoscience and Remote Sensing, 39(2), 321–329.
11. Fauvel, M., Tarabalka, Y., Benediktsson, J. A., Chanussot, J., & Tilton, J. C. (2013). Advances in spectral-spatial classification of hyperspectral images. Proceedings of the IEEE, 101(3), 652–675.
12. Freeman, A., & Durden, S. L. (1998). A three-component scattering model for polarimetric SAR data. IEEE Transactions on Geoscience and Remote Sensing, 36(3), 963–973.
13. Freund, Y., & Schapire, R. E. (1996). Experiments with a new boosting algorithm. In ICML (Vol. 96, pp. 148–156).
14. Fukuda, S., & Hirosawa, H. (2001). Support vector machine classification of land cover: application to polarimetric SAR data. In Geoscience and Remote Sensing Symposium, 2001. IGARSS’01. IEEE 2001 International (Vol. 1, pp. 187–189): IEEE.
15. Ho, T. K. (1998). The random subspace method for constructing decision forests. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8), 832–844.
16. Holm, W., & Barnes, R. M. (1988). On radar polarization mixed target state decomposition techniques. In Radar Conference, 1988., Proceedings of the 1988 I.E. National (pp. 249–254): IEEE.
17. Hong, G., Kui, Y., & YouLiang, J. (2012). Segmentation of Polarimetric sar image using object-oriented strategy. In Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on (pp. 1–5): IEEE
18. Hughes, G. P. (1968). On the mean accuracy of statistical pattern recognizers. IEEE Transactions on Information Theory, 14(1), 55–63.
19. Huynen, J. R. (1970). Phenomenological theory of radar targets. TU Delft, Delft University of Technology
20. Jain, A., & Zongker, D. (1997). Feature selection: evaluation, application, and small sample performance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(2), 153–158.
21. Krogager, E. (1990). New decomposition of the radar target scattering matrix. Electronics Letters, 26(18), 1525–1527.
22. Lee, J.-S., Grunes, M. R., Ainsworth, T. L., Du, L.-J., Schuler, D. L., & Cloude, S. R. (1999a). Unsupervised classification using polarimetric decomposition and the complex Wishart classifier. IEEE Transactions on Geoscience and Remote Sensing, 37(5), 2249–2258.
23. Lee, J.-S., Grunes, M. R., & De Grandi, G. (1999b). Polarimetric SAR speckle filtering and its implication for classification. IEEE Transactions on Geoscience and Remote Sensing, 37(5), 2363–2373.
24. Lee, J., Grunes, M., Pottier, E., & Ferro-Famil, L. (2001). Segmentation of polarimetric SAR images. In International Geoscience and Remote Sensing Symposium (Vol. 1, pp. I: 414–416).
25. Li, H., Gu, H., Han, Y., & Yang, J. (2008). Object-oriented classification of polarimetric SAR imagery based on statistical region merging and support vector machine. In Earth Observation and Remote Sensing Applications, 2008. EORSA 2008. International Workshop on (pp. 1–6): IEEE.
26. Ma, X., Shen, H., Yang, J., Zhang, L., & Li, P. (2014). Polarimetric-spatial classification of SAR images based on the fusion of multiple classifiers.
27. Maghsoudi, Y. (2011). Analysis of Radarsat-2 full polarimetric data for forest mapping.
28. Maghsoudi, Y., Collins, M., & Leckie, D. G. (2012). Polarimetric classification of Boreal forest using nonparametric feature selection and multiple classifiers. International Journal of Applied Earth Observation and Geoinformation, 19, 139–150.
29. Salehi, M., Sahebi, M. R., & Maghsoudi, Y. (2014). Improving the Accuracy of urban land cover classification using Radarsat-2 PolSAR data.
30. Steele, B. M. (2000). Combining multiple classifiers: an application using spatial and remotely sensed information for land cover type mapping. Remote Sensing of Environment, 74(3), 545–556.
31. Van Zyl, J. J. (1989). Unsupervised classification of scattering behavior using radar polarimetry data. IEEE Transactions on Geoscience and Remote Sensing, 27(1), 36–45.
32. Von Neumann, J. (1941). Distribution of the ratio of the mean square successive difference to the variance. Annals of Mathematical Statistics, 12(4), 367–395.
33. Wu, T.-F., Lin, C.-J., & Weng, R. C. (2004). Probability estimates for multi-class classification by pairwise coupling. Journal of Machine Learning Research, 5, 975–1005.
34. Wu, Y., Ji, K., Yu, W., & Su, Y. (2008). Region-based classification of polarimetric SAR images using Wishart MRF. IEEE Geoscience and Remote Sensing Letters, 5(4), 668–672.
35. Yamaguchi, Y., Moriyama, T., Ishido, M., & Yamada, H. (2005). Four-component scattering model for polarimetric SAR image decomposition. IEEE Transactions on Geoscience and Remote Sensing, 43(8), 1699–1706.
36. Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., & Schirokauer, D. (2006). Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogrammetric Engineering & Remote Sensing, 72(7), 799–811.