Application of support vector machines for automatic compliance monitoring of the Conservation Reserve Program (CRP) tracts

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 1, Issue , 2004, Pages 242-245

  Cherian, Ginto ^a   Song, Xiaomu ^a   Fan, Guoliang ^a   Rao, Mahesh N ^b  

^a Oklahoma State University   (United States)

^b OKLAHOMA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMON LAND UNIT (CLU); CONSERVATION RESERVE PROGRAM (CRP); TWO-CLASS SUPPORT VECTOR MACHINE (TCSVM); UNITED STATES DEPARTMENT OF AGRICULTURE (USDA);

ALGORITHMS; COMPUTER SIMULATION; COST EFFECTIVENESS; DATA ACQUISITION; GEOGRAPHIC INFORMATION SYSTEMS; PHOTOINTERPRETATION;

REMOTE SENSING;

EID: 15944390981     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. G. M. Foody and A. Mathur, "A relative evaluation of multiclass image classification by support vector machines," IEEE Trans. Geosci. Remote Sensing, vol. PP. no. 99, pp. 1-9, 2004, accepted for future publication.
2. I. Keuchel, S. Naumann, M. Heiler, and A. Siegmund, "Automatic land cover analysis for tenerife by supervised classification using remotely sensed data," Remote Sensing of Environment, vol. 86, no. 4, pp. 530-541, August 2003.
3. C. Huang, L. S. Davis, and J. R. G. Townshend, "An assessment of support vector machines for land cover classification," International Journal of Remote Sensing, vol. 23, no. 4, pp. 725-749, Feb. 2002.
4. J. A. Gualtieri and R. F. Cromp, "Support vector machines for hyperspectral remote sensing classification," in in Proc. 27th SPIE AIPR Workshop, 1998.
5. L. Hermes, D. Frieauff, J. Puzicha, and J. M. Buhmann, "Support vector machines for land usage classification in Landsat TM imagery," in Proc. IEEE Int. Geoscience and Remote Sensing Symposium, vol. 1, July 1999, pp. 348-350.
6. B. Schölkopf, J. C. Platt, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson, "Estimating the support of a high-dimensional distribution," Neural Computation, vol. 13, no. 7, pp. 1443-1471, 2001.
7. P. Hayton. B. Schölkopf, L. Tarassenko, and P. Anuzis, "Support vector novelty detection applied to jet engine vibration spectra," Neural Information Processing Systems. London, pp. 946-952, 2000.
8. D. M. J. Tax, "One-class classification." Ph.D. dissertation, Technische Universiteit Delft, The Netherlands, 2001.
9. D. M. J. Tax and R. P. W. Duin, "Support vector data description," Machine Learning, vol. 54, no. 1, pp. 45-66, Jan. 2004.
10. X. Song, G. Fan, and M. Rao, "Machine learning approaches for multi-source geospatial data classification with application to crp mapping in texas county, Oklahoma," in Proc. IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, NASA Goddard Visitor Center, Washington DC, October 2003.
11. Conservation Reserve Program, http://www.fsa.usda.gov/dafp/cepd/crp.htm.
12. J. Heald, "Usda establishes a common land unit," in ArcUser Online, March-April 2002, http://www.esri.com/news/arcuser/0402/usda.html.
13. V. N. Vapnik, The Nature of Statistical Learning Theory. New York: Spinger-Verlag. 1995.
14. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol. 2, no. 2, pp. 121-167, Jun. 1998.
15. B. Schölkopf, "Support vector learning," Ph.D. dissertation, Technischen Universität Berlin, 1997.
16. G. Ratsch. S. Mika, B. Scholkopf. and K.-R. Müller, "Constructing boosting algorithms from svms: an application to one-class classification," IEEE Trans. Pattern Anal. Machine Intell., vol. 24. no. 9, pp. 1184-1199, Sept. 2002.