Vol. 55
Latest Volume
All Volumes
PIERM 127 [2024] PIERM 126 [2024] PIERM 125 [2024] PIERM 124 [2024] PIERM 123 [2024] PIERM 122 [2023] PIERM 121 [2023] PIERM 120 [2023] PIERM 119 [2023] PIERM 118 [2023] PIERM 117 [2023] PIERM 116 [2023] PIERM 115 [2023] PIERM 114 [2022] PIERM 113 [2022] PIERM 112 [2022] PIERM 111 [2022] PIERM 110 [2022] PIERM 109 [2022] PIERM 108 [2022] PIERM 107 [2022] PIERM 106 [2021] PIERM 105 [2021] PIERM 104 [2021] PIERM 103 [2021] PIERM 102 [2021] PIERM 101 [2021] PIERM 100 [2021] PIERM 99 [2021] PIERM 98 [2020] PIERM 97 [2020] PIERM 96 [2020] PIERM 95 [2020] PIERM 94 [2020] PIERM 93 [2020] PIERM 92 [2020] PIERM 91 [2020] PIERM 90 [2020] PIERM 89 [2020] PIERM 88 [2020] PIERM 87 [2019] PIERM 86 [2019] PIERM 85 [2019] PIERM 84 [2019] PIERM 83 [2019] PIERM 82 [2019] PIERM 81 [2019] PIERM 80 [2019] PIERM 79 [2019] PIERM 78 [2019] PIERM 77 [2019] PIERM 76 [2018] PIERM 75 [2018] PIERM 74 [2018] PIERM 73 [2018] PIERM 72 [2018] PIERM 71 [2018] PIERM 70 [2018] PIERM 69 [2018] PIERM 68 [2018] PIERM 67 [2018] PIERM 66 [2018] PIERM 65 [2018] PIERM 64 [2018] PIERM 63 [2018] PIERM 62 [2017] PIERM 61 [2017] PIERM 60 [2017] PIERM 59 [2017] PIERM 58 [2017] PIERM 57 [2017] PIERM 56 [2017] PIERM 55 [2017] PIERM 54 [2017] PIERM 53 [2017] PIERM 52 [2016] PIERM 51 [2016] PIERM 50 [2016] PIERM 49 [2016] PIERM 48 [2016] PIERM 47 [2016] PIERM 46 [2016] PIERM 45 [2016] PIERM 44 [2015] PIERM 43 [2015] PIERM 42 [2015] PIERM 41 [2015] PIERM 40 [2014] PIERM 39 [2014] PIERM 38 [2014] PIERM 37 [2014] PIERM 36 [2014] PIERM 35 [2014] PIERM 34 [2014] PIERM 33 [2013] PIERM 32 [2013] PIERM 31 [2013] PIERM 30 [2013] PIERM 29 [2013] PIERM 28 [2013] PIERM 27 [2012] PIERM 26 [2012] PIERM 25 [2012] PIERM 24 [2012] PIERM 23 [2012] PIERM 22 [2012] PIERM 21 [2011] PIERM 20 [2011] PIERM 19 [2011] PIERM 18 [2011] PIERM 17 [2011] PIERM 16 [2011] PIERM 14 [2010] PIERM 13 [2010] PIERM 12 [2010] PIERM 11 [2010] PIERM 10 [2009] PIERM 9 [2009] PIERM 8 [2009] PIERM 7 [2009] PIERM 6 [2009] PIERM 5 [2008] PIERM 4 [2008] PIERM 3 [2008] PIERM 2 [2008] PIERM 1 [2008]
2017-03-14
Evaluation of Hybrid Polarimetric Decomposition Techniques for Winter Crop Discrimination
By
Progress In Electromagnetics Research M, Vol. 55, 73-84, 2017
Abstract
In this paper we compare, using ISRO's RISAT-1 FRS-1 mode Compact Polarimetric (CL-Pol) data, two widely used hybrid polarimetric decomposition techniques, m-δ and m-χ decompositions, with regard to classification accuracy for various agricultural crops of north and west India. We show that the classification based on the m-χ decomposition results in better crop separability in general. But the crop stage and existence of orientating structures in the crops affects the efficacy of decomposition; a fact vividly brought out in this paper. Theoretical insights into the effectiveness of these decomposition techniques for different crop geometry are brought forth. We also compare the classification accuracy subsequent to polarimetric speckle filtering vis-a-vis spatial multilooking (downsampling). We show that usage of an appropriate polarimetric filter tends to produce comparable accuracy for most of the agricultural classes, as that of multilook case, without degrading spatial resolution. This work showcases a custom implementation of Stokes parameter based decomposition as well as POLSAR filter based on refined Lee algorithm, written in C and tailored to RISAT-1.
Citation
Sanid Chirakkal, Dipanwita Haldar, and Arundhati Misra, "Evaluation of Hybrid Polarimetric Decomposition Techniques for Winter Crop Discrimination," Progress In Electromagnetics Research M, Vol. 55, 73-84, 2017.
doi:10.2528/PIERM17011603
References

1. Raney, R. K., "Hybrid-polarimetry SAR architecture," IEEE Trans. Geosci. Remote Sens., Vol. 45, No. 11, 3397-3404, Nov. 2007.
doi:10.1109/TGRS.2007.895883

2. Raney, R. K., "Dual-polarized SAR and stokes parameters," IEEE Geosci. Remote Sens. Lett., Vol. 3, No. 3, 317-319, Jul. 2006.
doi:10.1109/LGRS.2006.871746

3. Charbonneau, F., "Compact polarimetry: General results," Proceedings of the 2nd Compact Polarimetry Workshop, Ottawa, Ont, January 6-7, 2009.

4. Charbonneau, F. J., B. Brisco, R. K. Raney, H. McNaim, C. Liu, P. W. Vachon, J. Shang, R. De Abreau, C. Champagne, A. Merzouki, and T. Geldsetzer, "Compact polarimetry overview and applications assessment," Can. J. Remote Sensing, Vol. 36, S298-S315, 2010.
doi:10.5589/m10-062

5. Dubois-Fernandez, P., J.-C. Souyris, S. Angelliaume, and F. Garestier, "The compact polarimetry alternative for spaceborne SAR at low frequency," IEEE Trans. Geosci. Remote Sens., Vol. 46, 3208-3222, 2008.
doi:10.1109/TGRS.2008.919143

6. Ainsworth, T. L., J. P Kelly, and J.-S. Lee, "Classification comparisons between dual-pol, compact polarimetry, and quad-pol imagery," ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 64, No. 5, 464-471, 2009.
doi:10.1016/j.isprsjprs.2008.12.008

7. Lee, J. S., "Digital image enhancement and noise filtering by use of local statistics," IEEE Transactions on Pattern Analysis and Machine Intelliegence, Vol. 2, No. 2, 165-168, 1980.
doi:10.1109/TPAMI.1980.4766994

8. Lee, J. S., "Refined filtering of image noise using local statistics," Computer Vision, Graphics, and Image Processing, Vol. 15, 380-389, 1981.
doi:10.1016/S0146-664X(81)80018-4

9. Lee, J. S., M. R. Grunes, and G. De Grandi, "Polarimetric SAR speckle filtering and its implication for classification," IEEE Transactions of Geoscience and Remote Sensing, Vol. 37, No. 5, 2363-2373, 1999.
doi:10.1109/36.789635

10. Lee, J. S. and E. Pottier, Polarimetric Radar Imaging: From Basics to Applications, CRC Press, 2009.
doi:10.1201/9781420054989

11. Stratton, J. A., Electromagnetic Theory, McGraw-Hill, New York, 1941.

12. Raney, R. K., "Decomposition of hybrid-polarity SAR data," PolIn-SAR 2007: Proceedings of the 3rd International Workshop on Science and Applications, Frascati, Italy, January 22-26, 2007, H. Lacoste and L. Ouwehand (eds.), ESA Publications, ESTEC, SP-644, Noordwijk, The Netherlands, 2007.

13. Jayasri, P. V., H. S. V. Usha Sundari, E. V. S. Sita Kumari, and A. V. V. Prasad, "M-delta decomposition of hybrid dual-polarimetric RISAT-1 SAR data," 9th International Radar Symposium India, 2013.

14. Lardeux, C., D. Niamen, J. B. Routier, A. Giraud, P. L. Frison, E. Pottier, and J. P. Rudant, "Assessment of compact polarimetry over different tropical environment and dataset," Geoscience and Remote Sensing Symposium (IGARSS), 3279-3282, 2010.

15. Lardeux, C., P.-L. Frison, C. Tison, J.-C. Souyris, B. Stoll, B. Fruneau, and J.-P. Rudant, "Support vector machine for multifrequency SAR polarimetric data classification," IEEE Trans. GRS, Vol. 47, No. 12, 4143-4152, 2009.

16. Tapan, M., S. S. Rana, N. M. Desai, D. B. Dave, Rajeevjyoti, R. K. Arora, C. V. N. Rao, B. V. Bakori, R. Neelakantan, and J. G. Vachchani, "Synthetic Aperture Radar payload on-board RISAT-1: configuration, technology and performance," Current Science, Vol. 104, No. 4, 2013.

17. Haldar, D., A. Das, S. Mohan, O. Pal, R. S. Hooda, and M. Chakraborty, "Assessment of L-band SAR data at different polarization combinations for crop and other landuse classification," Progress In Electromagnetics Research B, Vol. 36, 303-321, 2012.
doi:10.2528/PIERB11071106

18. Haldar, D., M. Chakraborty, K. R. Manjunath, and J. S. Parihar, "Role of polarimetric SAR data for discrimination/biophysical parameters of crops based on canopy architecture," Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XL-8, ISPRS Technical Commission VIII Symposium, 737-744, Hyderabad, India, 2014.
doi:10.5194/isprsarchives-XL-8-737-2014

19. Congalton, R. G., "A review of assessing the accuracy of classifications of remotely sensed data," Remote Sens. Environ., Vol. 37, 35-46, 1991.
doi:10.1016/0034-4257(91)90048-B

20. Kumar, V. and Y. S. Rao, "Comparative analysis of RISAT-1 and simulated RADARSAT-2 hybrid polarimetric SAR data for different land features," Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XL-8, ISPRS Technical Commission VIII Symposium, Hyderabad, India, 2014.