Unsupervised polarimetric SAR urban area classification based on model-based decomposition with cross scattering

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 116, Issue , 2016, Pages 86-100

  Xiang, Deliang ^a,b   Tang, Tao ^b   Ban, Yifang ^a   Su, Yi ^b   Kuang, Gangyao ^b  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Cross scattering matrix; K means classifier; Model based decomposition; Polarimetric SAR (PolSAR); Urban area classification

Indexed keywords

MATRIX ALGEBRA; POLARIMETERS; SATELLITE COMMUNICATION SYSTEMS;

K-MEANS; MODEL BASED DECOMPOSITIONS; POLARIMETRIC SAR; SCATTERING MATRICES; URBAN AREA CLASSIFICATION;

SYNTHETIC APERTURE RADAR;

AIRS; CLASSIFICATION; NUMERICAL METHOD; NUMERICAL MODEL; PALSAR; RADARSAT; SCATTERING; SYNTHETIC APERTURE RADAR; UNSUPERVISED CLASSIFICATION; URBAN AREA; VEGETATION COVER;

EID: 84962538521     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2016.03.009     Document Type: Article

References (30)

1. Ainsworth T.L., Schuler D.L., Lee J.S. Polarimetric SAR characterization of man-made structures in urban areas using normalized circular-pol correlation coefficients. Remote Sens. Environ. 2008, 112:2876-2885.
2. An W., Cui Y., Yang J. Three-component model-based decomposition for polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 2010, 48:2732-2739.
3. Antropov O., Rauste Y., Hme T. Volume scattering modeling in PolSAR decompositions: study of ALOS PALSAR data over boreal forest. IEEE Trans. Geosci. Remote Sens. 2011, 49:3838-3848.
4. Chen S., Li Y., Wang X. Modeling and interpretation of scattering mechanisms in polarimetric synthetic aperture radar: advances and perspectives. Signal Process. Mag., IEEE 2014, 31:79-89.
5. Chen S.-W., Ohki M., Shimada M., Sato M. Deorientation effect investigation for model-based decomposition over oriented built-up areas. IEEE Geosci. Remote Sens. Lett. 2013, 10:273-277.
6. Chen S.W., Sato M. Tsunami damage investigation of built-up areas using multi-temporal spaceborne full polarimetric SAR images. IEEE Trans. Geosci. Remote Sens. 2013, 51:1985-1997.
7. Cheng X., Huang W. A decomposition-free scattering mechanism classification method for PolSAR images with Neumann's model. Remote Sens. Lett. 2013, 4:1176-1184.
8. Dabboor M., Collins M.J., Karathanassi V., Braun A. An unsupervised classification approach for polarimetric SAR data based on the Chernoff distance for complex Wishart distribution. IEEE Trans. Geosci. Remote Sens. 2013, 51:4200-4213.
9. Deng L., Wang C. Improved building extraction with integrated decomposition of time-frequency and entropy-alpha using polarimetric SAR data. IEEE J. Sel. Topics Appl. Earth Obser. Remote Sens. (JSTARS) 2014, 7:4058-4068.
10. Deng L., Yan Y.-N., Sun C. Use of sub-aperture decomposition for supervised PolSAR classification in urban area. Remote Sens. 2015, 7:1380-1396.
11. Freeman A., Durden S.L. A three-component scattering model for polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 1998, 36:963-973.
12. Hong S.-H., Wdowinski S. Double-bounce component in cross-polarimetric SAR from a new scattering target decomposition. IEEE Trans. Geosci. Remote Sens. 2014, 52:3039-3051.
13. Kajimoto M., Susaki J. Urban-area extraction from polarimetric SAR images using polarization orientation angle. IEEE Geosci. Remote Sens. Lett. 2013, 10:337-341.
14. Lee J.S. On the estimation of radar polarization orientation shifts induced by terrain slopes. IEEE Trans. Geosci. Remote Sens. 2002, 40:30-41.
15. Lee J., Pottier E. Polarimetric Radar Imaging: From Basics to Applications 2009, CRC Press, FL, USA. B. Raton (Ed.).
16. Moriyama T., Uratsuka S., Umehara T., Maeno H., Satake M., Nadai A., Nakamura K. Polarimetric SAR image analysis using model fit for urban structures. IEICE Trans. Commun. 2005, E88-B:1234-1242.
17. Niu X., Ban Y. Multitemporal RADARSAT-2 polarimetric SAR data for urban land cover classification using an object-based support vector machine and a rule-based approach. Int. J. Remote Sens. 2013, 34:1-26.
18. Salehi M., Sahebi M.R., Maghsoudi Y. Improving the accuracy of urban land cover classification using Radarsat-2 PolSAR data. IEEE J. Sel. Topics Appl. Earth Obser. Remote Sens. (JSTARS) 2014, 7:1-8.
19. Sato A., Yamaguchi Y. Four-component scattering power decomposition with extended volume scattering model. IEEE Geosci. Remote Sens. Lett. 2012, 9:166-170.
20. Shan Z., Wang C., Zhang H., An W. Improved four-component model-based target decomposition for polarimetric SAR data. IEEE Geosci. Remote Sens. Lett. 2012, 9:75-79.
21. Shan Z., Zhang H., Wang C. Four-component model-based decomposition of polarimetric SAR data for special ground objects. IEEE Geosci. Remote Sens. Lett. 2012, 9:989-993.
22. Story M., Congalton R.G. Accuracy assessment-a users perspective. Photogramm. Eng. Remote Sens. 1986, 52:397-399.
23. Wu W., Guo H., Li X. Man-made target detection in urban areas based on a new azimuth stationarity extraction method. IEEE J. Sel. Topics Appl. Earth Obser. Remote Sens. (JSTARS) 2013, 6:1138-1146.
24. Yamaguchi Y. Disaster monitoring by fully polarimetric SAR data acquired with ALOS-PALSAR. Proc. IEEE 2012, 100:2851-2860.
25. Yamaguchi Y., Moriyama T., Ishido M., Yamada H. Four-component scattering model for polarimetric SAR image decomposition. IEEE Trans. Geosci. Remote Sens. 2005, 43:1699-1706.
26. Yamaguchi Y., Sato A., Boerner W.-M., Sato R., Yamada H. Four-component scattering power decomposition with rotation of coherency matrix. IEEE Trans. Geosci. Remote Sens. 2011, 49:2251-2258.
27. Yamaguchi Y., Yajima Y., Yamada H. A four-component decomposition of POLSAR images based on the coherency matrix. IEEE Geosci. Remote Sens. Lett. 2005, 3:292-296.
28. Yang W., Yin X., Song H., Liu Y., Xu X. Extraction of built-up areas from fully polarimetric SAR imagery via PU learning. IEEE J. Sel. Topics Appl. Earth Obser. Remote Sens. (JSTARS) 2014, 7:1207-1216.
29. Zhang L., Zou B., Cai H., Zhang Y. Multiple-component scattering model for polarimetric SAR image decomposition. IEEE Geosci. Remote Sens. Lett. 2008, 5:603-607.
30. Zhang L., Zou B., Zhang J., Zhang Y. Support vector machine using multiple-component scattering model and texture features. EURASIP J. Adv. Signal Process. 2010, 2010:1-9.