Spectral Mixture Analysis Using Modified IEA Algorithm for Forest Classification |
Song, Ahram
(Department of Civil and Environmental Engineering, Seoul National University)
Han, Youkyung (Department of Civil and Environmental Engineering, Seoul National University) Kim, Younghyun (Department of Civil and Environmental Engineering, Seoul National University) Kim, Yongil (Department of Civil and Environmental Engineering, Seoul National University) |
1 | Neville, R. A., K. Staennz, T. Szeredi, J. Lefebvre and P. Hauff, 1999, Automatic endmember extraction from hyperspectral data for mineral exploration, Proc. of 21st Canada Symposium on Remote Sensing, Ottawa, ON, Canada, pp.21-24. |
2 | Plaza, A. and C.I. Chang, 2005, An improved N-FINDR algorithm in implementation, Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, SPIE Symposium on Defense and Security, SPIE, Orlando, Florida, vol. 5806, pp. 298-306. |
3 | Roberts, D.A., M. Gardner, R. Church, S. Ustin, G. Scheer and R.O. Green, 1998, Mapping chaparral in the santa monica mountains using multiple endmember spectral mixture models, Remote Sensing of Environment, 65(3): 267-279. DOI ScienceOn |
4 | Shin, J., S. Kim, J. Yoon, T. Kim and K. Lee, 2006, Spectral mixture analysis using hyperspectral image for hydrological land cover classification in urban area, Korean Journal of Remote Sensing, 22(6): 565-574. 과학기술학회마을 DOI |
5 | Song, A., A. Chang, J. Choi and Y. Kim, 2013, Application evaluation of endmember extracton algorithm on the AISA hyperspectral images, Korean Journal of Remote Sensing, 29(5): 527-535. DOI ScienceOn |
6 | Thoreau, R.T., C.C. Nicholas, R.G. Nicholas and A.V. James, 2009, Extraction urban vegetation characteristic using spectral mixture analysis and decision tree classifications, Remote Sensing of Environment, 113(2): 398-407. DOI ScienceOn |
7 | Wu, C. and A.T. Murray, 2003, Estimating impervious surface distribution by spectral mixture analysis, Remote Sensing of Environment 84(4): 493-505. DOI ScienceOn |
8 | Chang, C.I., 1999, Spectral information divergence for hyperspectral image analysis, Proc. of International Geoscience and Remote Sensing Symposium, Hamburg, Germany, June 28-July 2, pp.509-511. |
9 | Choi, J., D. Kim, B. Lee, Y. Kim and K. Yu, 2006, Hyperspectral image fusion algorithm based on two-stage spectral unmixing method, Korean Journal of Remote Sensing, 22(4): 295-304. 과학기술학회마을 DOI |
10 | Jeong, S., C. Park and S. Kim, 2006, Land cover classification of the Korean penisula using linear spectral mixture analysis of MODIS multi-temporal data, Korean Journal of Remote Sensing, 22(6): 553-563. DOI |
11 | Kim, D., 2003, A study on sub-pixel detection for hyperspectral imagery using the linear spectral mixing model, Master's Thesis, Seoul National University. |
12 | Kim, K., 2011, A modified iterative N-FINDR algorithm for fully automatic extraction of endmembers from hyperspectral imagery, Korean Journal of Remote Sensing, 27(5): 565-572. 과학기술학회마을 DOI ScienceOn |
13 | Kim, S. and K. Lee, 2004, Application of linear spectral mixture analysis to geological thematic mapping using LANDSAT 7 ETM+ and ASTER satellite imageries, Korean Journal of Remote Sensing, 20(6) : 369-382. 과학기술학회마을 DOI |
14 | Lillesand, T.M., and R.W. Kiefer, 1979, Remote sensing and image interpretation, John Wiley & Sons, New York, USA. |
15 | Kim, J., K. Hwang and S. Kim, 2013, The evaluation of correlation between disturbance intensity and stand development by natural forest community type classification, Journal of Forest Science, 29(3): 219-225. 과학기술학회마을 DOI ScienceOn |
16 | Kim, S., K. Lee, J. Ma and M. Kook, 2005, Current status of hyperspectral remote sensing: principle, data processing techniques, and applications, Korean Journal of Remote Sensing, 21(4): 341-369. 과학기술학회마을 DOI |
17 | Lee, J. and K. Lee, 2003, Analysis of forest cover information extracted by spectral mixture analysis, Korean Journal of Remote Sensing, 19(6): 411-419. 과학기술학회마을 DOI |
18 | Ministry of Environment, 2002, Construction of landcover map using remote sensing image. |