Enhanced decision tree ensembles for land-cover mapping from fully polarimetric SAR data

References

• Ainsworth, T. L., J. P. Kelly, and J. S. Lee. 2009. “Classification Comparisons between Dual-Pol, Compact Polarimetric and Quad-Pol SAR Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 64 (5): 464–471. doi:10.1016/j.isprsjprs.2008.12.008.
   Web of Science ®Google Scholar
• Alberga, V. 2007. “A Study of Land Cover Classification Using Polarimetric SAR Parameters.” International Journal of Remote Sensing 28 (17): 3851–3870. doi:10.1080/01431160601075541.
   Web of Science ®Google Scholar
• Alberga, V., G. Satalino, and D. K. Staykova. 2008. “Comparison of Polarimetric SAR Observables in Terms of Classification Performance.” International Journal of Remote Sensing 29 (14): 4129–4150. doi:10.1080/01431160701840182.
   Web of Science ®Google Scholar
• Atwood, D. K., D. Small, and R. Gens. 2012. “Improving PolSAR Land Cover Classification with Radiometric Correction of the Coherency Matrix.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5: 848–856. Accessed 20 June 2016. http://earth.eo.esa.int/PolSARpro/datasets.html. Accessed April 2014. http://uavsar.jpl.nasa.gov/cgi-bin/data.pl
   Web of Science ®Google Scholar
• Bai, Y., D. Peng, X. Yang, L. Chen, and W. Yang. 2014. “Supervised Feature Selection for Polarimetric SAR Classification.” 2014 12th International Congress on Signal Processing (ICSP), IEEE, Hangzhou, China. 1006–1010.
   Google Scholar
• Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Bruzzone, L., M. Marconcini, U. Wegmüller, and A. Wiesmann. 2004. “An Advanced System for the Automatic Classification of Multitemporal SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 42: 1321–1334. doi:10.1109/TGRS.2004.826821.
   Web of Science ®Google Scholar
• Cloude, S. R., and E. Pottier. 1996. “A Review of Target Decomposition Theorems in Radar Polarimetry.” IEEE Transactions on Geoscience and Remote Sensing 34 (2): 498–518. doi:10.1109/36.485127.
   Web of Science ®Google Scholar
• Cloude, S. R., and E. Pottier. 1997. “An Entropy Based Classification Scheme for Land Applications of Polarimetric SAR.” IEEE Transactions on Geoscience and Remote Sensing 35 (1): 68–78. doi:10.1109/36.551935.
   Web of Science ®Google Scholar
• Congalton, R. G. 1991. “A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data.” Remote Sensing of Environment 37 (1): 35–46. doi:10.1016/0034-4257(91)90048-B.
   Web of Science ®Google Scholar
• Dargahi, A., Y. Maghsoudi, and A. A. Abkar. 2013. “Supervised Classification of Polarimetric SAR Imagery Using Temporal and Contextual Information.” Remote Sensing Spatial Information Science, Tehran, Iran, October 5–8, XL-1/W3:107–110.
   Google Scholar
• Deschamps, B., H. McNairn, J. Shang, and X. Jiao. 2012. “Towards Operational Radar-Only Crop Type Classification: Comparison of a Traditional Decision Tree with a Random Forest Classifier.” Canadian Journal of Remote Sensing 38 (1): 60–68. doi:10.5589/m12-012.
   Web of Science ®Google Scholar
• Du, P., A. Samat, B. Waske, S. Liu, and Z. Li. 2015. “Random Forest and Rotation Forest for Fully Polarized SAR Image Classification Using Polarimetric and Spatial Features.” ISPRS Journal of Photogrammetry and Remote Sensing 105: 38–53. doi:10.1016/j.isprsjprs.2015.03.002.
   Web of Science ®Google Scholar
• Du, P., A. Samat, P. Gamba, and X. Xie. 2014. “Polarimetric SAR Image Classification by Boosted Multiple-Kernel Extreme Learning Machines with Polarimetric and Spatial Features.” International Journal of Remote Sensing 35 (23): 7978–7990. doi:10.1080/2150704X.2014.978952.
   Web of Science ®Google Scholar
• Du, P., J. Xia, W. Zhang, K. Tan, Y. Liu, and S. Liu. 2012. “Multiple Classifier System for Remote Sensing Image Classification: A Review.” Sensors 12 (4): 4764–4792. doi:10.3390/s120404764.
   PubMed Web of Science ®Google Scholar
• Ferro-Famil, L., E. Pottier, and J. S. Lee. 2001. “Unsupervised Classification of Multifrequency and Fully Polarimetric SAR Images Based on H/A/Alpha-Wishart Classifier.” IEEE Transactions on Geoscience and Remote Sensing 39 (11): 2332–2342. doi:10.1109/36.964969.
   Web of Science ®Google Scholar
• Freeman, A., and S. L. Durden. 1998. “A Three-Component Scattering Model for Polarimetric SAR Data.” IEEE Transactions on Geoscience and Remote Sensing 36 (3): 963–973. doi:10.1109/36.673687.
   Web of Science ®Google Scholar
• Fukuda, S., and H. Hirosawa. 2001. “Support Vector Machine Classification of Land Cover: Application to Polarimetric SAR Data.” Geoscience Remote Sensing Symposium 2001. IGARSS ’01. IEEE 2001 International 1: 187–189.
   Google Scholar
• Gao, L., and Y. Ban. 2008. “Investigating the Performance of SAR Polarimetric Features in Land-Cover Classification.” In International Society for Photogrammetry and Remote Sensing, Part B6b. Beijing, Vol. XXXVII: 3–11.
   Google Scholar
• Habibi, M., M. R. Sahebi, Y. Maghsoudi, and S. Ghayourmanesh. 2016. “Classification of Polarimetric SAR Data Based on Object-Based Multiple Classifiers for Urban Land-Cover.” Journal of the Indian Society of Remote Sensing 44 (6): 855–863. doi:10.1007/978-0-387-84858-7.
   Web of Science ®Google Scholar
• Haddadi, G. A., M. Reza Sahebi, and A. Mansourian. 2011. “Polarimetric SAR Feature Selection Using a Genetic Algorithm.” Canadian Journal of Remote Sensing 37 (1): 27–36. doi:10.5589/m11-013.
   Web of Science ®Google Scholar
• Hara, Y., R. G. Atkins, S. H. Yueh, R. T. Shin, and J. A. Kong. 1994. “Application of Neural Networks to Radar Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 32 (1): 100–109. doi:10.1109/36.285193.
   Web of Science ®Google Scholar
• Hastie, T. J., R. J. Tibshirani, and J. H. Friedman. 2009. The Elements Of Statistical Learning: Data Mining, Inference, and Prediction. Springer. doi:10.1007/978-0-387-84858-7.
   Google Scholar
• He, H., and E. A. Garcia. 2009. “Learning from Imbalanced Data.” IEEE Transactions on Knoweledge and Data Engineering 21 (9): 1263–1284. doi:10.1109/TKDE.2008.239.
   Web of Science ®Google Scholar
• Jafari, M., Y. Maghsoudi, and M. J. Valadan Zoej. 2015. “A New Method for Land Cover Characterization and Classification of Polarimetric SAR Data Using Polarimetric Signatures.” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 8 (7): 3595–3607. doi:10.1109/JSTARS.2014.2387374.
   Web of Science ®Google Scholar
• Khoshelham, K., C. Nardinocchi, E. Frontoni, A. Mancini, and P. Zingaretti. 2010. “Performance Evaluation of Automated Approaches to Building Detection in Multi-Source Aerial Data.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 123–133. doi:10.1016/j.isprsjprs.2009.09.005.
   Web of Science ®Google Scholar
• Khosravi, I., and M. Mohammad-Beigi. 2014. “Multiple Classifier Systems for Hyperspectral Remote Sensing Data Classification.” Journal of the Indian Society of Remote Sensing 42 (2): 423–428. doi:10.1007/s12524-013-0327-7.
   Web of Science ®Google Scholar
• Krogager, E. 1990. “New Decomposition of the Radar Target Scattering Matrix.” Electronics Letters 26 (18): 1525–1527. doi:10.1049/el:19900979.
   Web of Science ®Google Scholar
• Lardeux, C., P. L. Frison, C. Tison, J. C. Souyris, B. Stoll, B. Fruneau, and J. P. Rudant. 2009. “Support Vector Machine for Multifrequency SAR Polarimetric Data Classification.” IEEE Transactions on Geoscience and Remote Sensing 47 (12): 4143–4152. doi:10.1109/TGRS.2009.2023908.
   Web of Science ®Google Scholar
• Lee, J. S., and E. Pottier. 2009. Polarimetric Radar Imaging: From Basics to Applications. Boca Raton, FL: CRC press. doi:10.1201/9781420054989.
   Google Scholar
• Lee, J. S., M. R. Grunes, and G. De Grandi. 1999. “Polarimetric SAR Speckle Filtering and Its Implication for Classification.” IEEE Transactions on Geoscience and Remote Sensing 37 (5): 2363–2373. doi:10.1109/36.789635.
   Web of Science ®Google Scholar
• Lee, J. S., M. R. Grunes, and R. Kwok. 1994. “Classification of Multi-Look Polarimetric SAR Imagery Based on Complex Wishart Distribution.” International Journal of Remote Sensing 15 (11): 2299–2311.
   Web of Science ®Google Scholar
• Longadge, R., and S. Dongre. 2013. “Class Imbalance Problem in Data Mining Review.” International Journal of Computer Science and Network 2 (1): 83–87.
   Google Scholar
• Lonnqvist, A., Y. Rauste, M. Molinier, and T. Hame. 2010. “Polarimetric SAR Data in Land Cover Mapping in Boreal Zone.” IEEE Transactions on Geoscience and Remote Sensing 48 (10): 3652–3662. doi:10.1109/TGRS.2010.2048115.
   Web of Science ®Google Scholar
• Ma, X., H. Shen, J. Yang, L. Zhang, and P. Li. 2014. “Polarimetric-Spatial Classification of SAR Images Based on the Fusion of Multiple Classifiers.” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 7 (3): 961–971. doi:10.1109/JSTARS.2013.2265331.
   Web of Science ®Google Scholar
• Maghsoudi, Y., M. Collins, and D. G. Leckie. 2012. “Polarimetric Classification of Boreal Forest Using Nonparametric Feature Selection and Multiple Classifiers.” Internationa Journal of Applied Earth Observation and Geoinformation 19: 139–150. doi:10.1016/j.jag.2012.04.015.
   Web of Science ®Google Scholar
• Mangai, U. G., S. Samanta, S. Das, and P. R. Chowdhury. 2010. “A Survey of Decision Fusion and Feature Fusion Strategies for Pattern Classification.” IETE Technical Review 27 (4): 293–307. doi:10.4103/0256-4602.64604.
   Web of Science ®Google Scholar
• McNairn, H., A. Kross, D. Lapen, R. Caves, and J. Shang. 2014. “Early Season Monitoring of Corn and Soybeans with TerraSAR-X and RADARSAT-2.” Internationa Journal of Applied Earth Observation and Geoinformation 28: 252–259. doi:10.1016/j.jag.2013.12.015.
   Web of Science ®Google Scholar
• Mishra, P., D. Singh, and Y. Yamaguchi. 2011. “Land Cover Classification of PALSAR Images by Knowledge Based Decision Tree Classifier and Supervised Classifiers Based on SAR Observables.” Progress in Electromagnetics Research 30: 47–70. doi:10.2528/PIERB11011405.
   Google Scholar
• Moriyama, T., S. Uratsuka, T. Umehara, M. Satake, A. Nadai, H. Maeno, and Y. Yamaguchi. 2004. “A Study on Extraction of Urban Areas from Polarimetric Synthetic Aperture Radar Image.” In Geoscience and Remote Sensing Symposium, 2004. IGARSS’04. Proceedings. 2004 IEEE International, Anchorage, AK. Vol. 1: 703–706. doi:10.1109/IGARSS.2004.1369127.
   Google Scholar
• Nghiem, S. V., S. H. Yueh, R. Kwok, and F. K. Li. 1992. “Symmetry Properties in Polarimetric Remote Sensing.” Radio Science 27 (5): 693–711. doi:10.1029/92RS01230.
   Web of Science ®Google Scholar
• Niu, X., and Y. Ban. 2014. “A Novel Contextual Classification Algorithm for Multitemporal Polarimetric SAR Data.” IEEE Geoscience and Remote Sensing Letters 11 (3): 681–685. doi:10.1109/LGRS.2013.2274815.
   Web of Science ®Google Scholar
• Pohjalainen, J., O. Räsänen, and S. Kadioglu. 2015. “Feature Selection Methods and Their Combinations in High-Dimensional Classification of Speaker Likability, Intelligibility and Personality Traits.” Computer Speech Language 29 (1): 145–171. doi:10.1016/j.csl.2013.11.004.
   Web of Science ®Google Scholar
• Qi, Z., A. G.-O. Yeh, X. Li, and X. Zhang. 2015. “A Three-Component Method for Timely Detection of Land Cover Changes Using Polarimetric SAR Images.” ISPRS Journal of Photogrammetry and Remote Sensing 107: 3–21. doi:10.1016/j.isprsjprs.2015.02.004.
   Web of Science ®Google Scholar
• Qi, Z., A. G.-O. Yeh, X. Li, and Z. Lin. 2012. “A Novel Algorithm for Land Use and Land Cover Classification Using RADARSAT-2 Polarimetric SAR Data.” Remote Sensing of Environment 118: 21–39. doi:10.1016/j.rse.2011.11.001.
   Web of Science ®Google Scholar
• Räsänen, O., and J. Pohjalainen. 2013. “Random Subset Feature Selection in Automatic Recognition of Developmental Disorders, Affective States, and Level of Conflict from Speech.” In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Lyon, France. 210–214.
   Google Scholar
• Salehi, M., M. R. Sahebi, and Y. Maghsoudi. 2014. “Improving the Accuracy of Urban Land Cover Classification Using Radarsat-2 PolSAR Data.” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 7 (4): 1394–1401. doi:10.1109/JSTARS.2013.2273074.
   Web of Science ®Google Scholar
• Sánchez-Lladó, F. J., G. Pajares, and C. López-Martínez. 2011. “Improving the Wishart Synthetic Aperture Radar Image Classifications through Deterministic Simulated Annealing.” ISPRS Journal of Photogrammetry and Remote Sensing 66 (6): 845–857. doi:10.1016/j.isprsjprs.2011.09.007.
   Web of Science ®Google Scholar
• Senliol, B., G. Gulgezen, L. Yu, and Z. Cataltepe. 2008. “Fast Correlation Based Filter (FCBF) with a Different Search Strategy.” International Symposium on Computer and Information Sciences, Istanbul, Turkey, October 27–29. 27–29. doi:10.1109/iscis.2008.4717949
   Google Scholar
• Shah Hosseini, R., I. Entezari, S. Homayouni, M. Motagh, and B. Mansouri. 2011. “Classification of Polarimetric SAR Images Using Support Vector Machines.” Canadian Journal of Remote Sensing 37 (2): 220–233. doi:10.5589/m11-029.
   Web of Science ®Google Scholar
• Shang, J., H. McNairn, B. Deschamps, and X. Jiao. 2011. “In-Season Crop Inventory Using Multi-Angle and Multi-Pass RADARTSAT-2 SAR Data over the Canadian Prairies.” In SPIE Optical Engineering Applications, San Diego, CA. Vol. 8156, 815604–815604. doi:10.1117/12.894211
   Google Scholar
• Shokrollahi, M., and H. Ebadi. 2016. “Improving the Accuracy of Land Cover Classification Using Fusion of Polarimetric SAR and Hyperspectral Images.” Journal of the Indian Society of Remote Sensing 44: 1017–1024. doi:10.1007/s12524-016-0559-4.
   Web of Science ®Google Scholar
• Song, C. J., S. Yun, and L. Hui. 2004. “Classification of Polarimetric SAR Imagery Based on Target Decomposition and Neural Network Classifier.” In Proceeding of ACRS ‘04, Chiang Mai, Thailand, November 2004.
   Google Scholar
• Souissi, B., A. P. Doulgeris, and T. Eltoft. 2007. “Classification Comparisons between Compact Polarimetric and Quad-Pol SAR Imagery.” POLINSAR, April 2015. Vol. 729.
   Google Scholar
• Souissi, B., M. Ouarzeddine, and A. Belhadj-Aissa. 2014. “Optimal SVM Classification for Compact Polarimetric Data Using Stokes Parameters.” Journal Mathematical Model Algorithms Operational Researcher 13: 433–446. doi:10.1007/s10852-013-9244-6.
   Google Scholar
• Tamiminia, H., S. Homayouni, H. McNairn, and A. Safari. 2017. “A Particle Swarm Optimized Kernel-Based Clustering Method for Crop Mapping from Multi-Temporal Polarimetric L-Band SAR Observations.” International Journal of Applied Earth Observation and Geoinformation 58: 201–212. doi:10.1016/j.jag.2017.02.010.
   Web of Science ®Google Scholar
• Uhlmann, S., and S. Kiranyaz. 2014. “Integrating Color Features in Polarimetric SAR Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 52: 2197–2206. doi:10.1109/TGRS.2013.2258675.
   Web of Science ®Google Scholar
• Waske, B., and M. Braun. 2009. “Classifier Ensembles for Land Cover Mapping Using Multitemporal SAR Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 64 (5): 450–457. doi:10.1016/j.isprsjprs.2009.01.003.
   Web of Science ®Google Scholar
• Waske, B., and S. Van Der Linden. 2008. “Classifying Multilevel Imagery from SAR and Optical Sensors by Decision Fusion.” IEEE Transactions on Geoscience and Remote Sensing 46 (5): 1457–1466. doi:10.1109/TGRS.2008.916089.
   Web of Science ®Google Scholar
• Xiangwei, X., K. Ji, H. Zou, and J. Sun. 2013. “Feature Selection and Weighted SVM Classifier-Based Ship Detection in PolSAR Imagery.” International Journal of Remote Sensing 34 (22): 7925–7944. doi:10.1080/01431161.2013.827812.
   Web of Science ®Google Scholar
• Xu, L., J. Li, and A. Brenning. 2014. “A Comparative Study of Different Classification Techniques for Marine Oil Spill Identification Using RADARSAT-1 Imagery.” Remote Sensing of Environment 141 (2014): 14–23. doi:10.1016/j.rse.2013.10.012.
   Web of Science ®Google Scholar
• Yamaguchi, Y., T. Moriyama, M. Ishido, and H. Yamada. 2005. “Four-Component Scattering Model for Polarimetric SAR Image Decomposition.” IEEE Transactions on Geoscience and Remote Sensing 43 (8): 1699–1706. doi:10.1109/TGRS.2005.852084.
   Web of Science ®Google Scholar
• Yu, L., and H. Liu. 2003. “Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution.” In Proceedings of the twentieth International Conference on Machine Learning (ICML-2003), Washington DC, Vol. 3, 856–863.
   Google Scholar
• Zeng, Z., H. Zhang, R. Zhang, and C. Yin. 2015. “A Novel Feature Selection Method Considering Feature Interaction.” Pattern Recognition 48 (8): 2656–2666. doi:10.1016/j.patcog.2015.02.025.
   Web of Science ®Google Scholar