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. https://doi.org/10.1016/j.isprsjprs.2008.12.008
- Angiulli, G., V. Barrile, and M. Cacciola, 2005. SAR imagery classification using multi-class support vector machines, Journal of Electromagnetic Waves and Applications, 19(14): 1865-1872. https://doi.org/10.1163/156939305775570558
- Ashutosh, S., 2002. Principal component-based algorithm on multispectral remote sensing data for spectral discrimination of tree cover from other vegetation types, Current Science, 82(1): 67-69.
- Bruzzone, L., D.F. Prieto, and S.B. Serpico, 1999. A neural-statistical approach to multitemporal and multisource remote-sensing image classification, IEEE Transactions on Geoscience and Remote Sensing, 37(3): 1350-1359. https://doi.org/10.1109/36.763299
- Burges, C.J.C., 1998. A tutorial on support vector machines for pattern recognition, Data Mining and Knowledge Discovery, 2: 121-167. https://doi.org/10.1023/A:1009715923555
- Camps-Valls, G. and L. Bruzzone, 2005. Kernel-based methods for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, 43(6): 1351-1362. https://doi.org/10.1109/TGRS.2005.846154
- Defries, R.S. and A.S. Belward, 2000. Global and regional land cover characterization from satellite data: An introduction to the Special Issue, International Journal of Remote Sensing, 21(6-7): 1083-1092. https://doi.org/10.1080/014311600210083
- Fukada, S. and H. Hirosawa, 2001. Support vector machine classification of land cover: Application to polarimetric SAR data, Proc. of 2001 International Geoscience and Remote Sensing Symposium, Sydney, Australia, Jul. 9-13, pp. 187-189.
- Henebry, G.M., 1997. Advantages of principal components analysis for land cover segmentation from SAR image series, Proc. of the third ERS symposium, Florence, Italy, Mar. 21-26, sp-414, pp. 175-178.
- Hepner, G.F., T. Logan, N. Ritter, and N. Bryant, 1989. Artificial neural network classification using a minimal training set: Comparison to conventional supervised classification, Photogrammetric Engineering and Remote Sensing, 56(4): 469-473.
- Hirosawa, Y., S.E. Marsh, and D.H. Kliman, 1996. Application of standardized principal component analysis to land-cover characterization using multitemporal AVHRR Data, Remote Sensing of Environment, 58(3): 267-281. https://doi.org/10.1016/S0034-4257(96)00068-5
- Jang, M.-W., Y.-H. Kim, N.-W. Park, and S.-Y. Hong, 2012. Mapping paddy rice varieties using multitemporal RADARSAT SAR images, Korean Journal of Remote Sensing, 28(6): 653-660. https://doi.org/10.7780/kjrs.2012.28.6.5
- Kuncheva, L.I., 2004. Combining Pattern Classifiers, Wiley, Hoboken, NJ, USA.
- Lee, J.-S., M.R. Grunes, T.L. Ainsworth, L.J. Du, D.L. Schuler, and S.R. Cloude, 1999. Unsupervised classification using polarimetric decompositions and the complex wishart classifier, IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2249-2258. https://doi.org/10.1109/36.789621
- Muraki, S., 1993. Volume data and wavelet transforms, IEEE Computer Graphics and Applications, 13(4): 50-56. https://doi.org/10.1109/38.219451
- Park, N.-W., H.Y. Yoo, Y. Kim, and S.-Y. Hong, 2012. Classification of remote sensing data using random selection of training data and multiple classifiers, Korean Journal of Remote Sensing, 28(5): 489-499. https://doi.org/10.7780/kjrs.2012.28.5.2
- Park, N.-W. and K.H. Chi, 2008. Integration of multitemporal/polarization C-band SAR data sets for land-cover classification, International Journal of Remote Sensing, 29(16): 4667-4688. https://doi.org/10.1080/01431160801947341
- Petrakos, M., J.A. Benediktsson, and I. Kanellopoulos, 2001. The effect of classifier agreement on the accuracy of the combined classifier in decision level fusion, IEEE Transactions on Geoscience and Remote Sensing, 39(11): 2539-2546. https://doi.org/10.1109/36.964992
- Serpico, S.B., L. Bruzzone, and F. Roli, 1996. An experimental comparison of neural and statistical non-parametric algorithms for supervised classification of remote-sensing images, Pattern Recognition Letters, 17(13): 1331-1341. https://doi.org/10.1016/S0167-8655(96)00090-6
- Skriver, H., J. Schou, and W. Dierking, 2000. Landcover mapping using multitemporal, dualfrequency polarimetric SAR data, Proc. of 2000 International Geoscience and Remote Sensing Symposium, Honolulu, HI, Jul. 24-28, vol.1, pp. 331-333.
- Sunar, F., 1998. An analysis of changes in a multidate data set: a case study in the Ikitelli area, Istanbul, Turkey, International Journal of Remote Sensing, 19(2): 225-235. https://doi.org/10.1080/014311698216215
- Tan, C.-P., J.-Y. Koay, K..-S. Lim, H.-T. Ewe, and H.-T. Chuah, 2007. Classification of multi-temporal SAR images for rice crops using combined entropy decomposition and support vector machine technique, Progress In Electromagnetics Research, 71: 19-39. https://doi.org/10.2528/PIER07012903
- Yoo, H.Y., N.-W. Park, S. Hong, K. Lee, and Y. Kim, 2013. Feature extraction and classification of multi-temporal SAR data using 3D wavelet transform, Korean Journal of Remote Sensing, 29(5): 569-579. https://doi.org/10.7780/kjrs.2013.29.5.12
Cited by
- 객체분할과 과거 토지피복 정보를 이용한 토지피복도 갱신 vol.33, pp.6, 2015, https://doi.org/10.7780/kjrs.2017.33.6.2.5