Integration of Soft and Hard Classifications Using Linear Spectral Mixture Model and Support Vector Machines

HU Tan-gao; PAN Yao-zhong; ZHANG Jin-shui; LI Ling-ling; LI Le

Journals >Spectroscopy and Spectral Analysis >Volume 31 >Issue 2 >Page 508 > Article

Spectroscopy and Spectral Analysis
Vol. 31, Issue 2, 508 (2011)

Integration of Soft and Hard Classifications Using Linear Spectral Mixture Model and Support Vector Machines

HU Tan-gao^*, PAN Yao-zhong, ZHANG Jin-shui, LI Ling-ling, and LI Le

Author Affiliations

[in Chinese]

show less

DOI: Cite this Article

HU Tan-gao, PAN Yao-zhong, ZHANG Jin-shui, LI Ling-ling, LI Le. Integration of Soft and Hard Classifications Using Linear Spectral Mixture Model and Support Vector Machines[J]. Spectroscopy and Spectral Analysis, 2011, 31(2): 508 Copy Citation Text

show less

References

[2] Das S K, Singh R. IEEE Transactions on Geoscience and Remote Sensing Letters, 2009, 6 (3): 453.

[3] Brandt Tso, Mather Paul M. Classification Methods for Remotely Sensed Data (Second Edition). London: CRC Press, 2009. 54.

[8] Ichoku C, Karnieli A. Remote Sensing Reviews, 1996， 13: 161.

[9] Shanmugam P, Ahn Y, Sanjeevi S. Ecological Modelling, 2006. 194: 379.

[11] Wu T. Journal of Machine Learning Research, 2004, 5: 975.

[14] Verhoeye J, Wulf R De. Remote Sensing of Environment, 2002, 79(1): 96.

[15] Chang C I, Plaza A. IEEE Geoscience and Remote Sensing Letters, 2006, 3(1): 63.

[16] Song Conghe, Dickinson Matthew B, Su Lihong. Remote Sensing of Environment, 2010, 114(5): 1099.

[17] Heinl M, Walde J, Tappeiner G. International Journal of Applied Earth Observation and Geoinformation, 2009, 11: 423.

Download Citation

Save the article for my favorites

Paper Information