TY - GEN
T1 - Multisource fusion for land cover classification using support vector machines
AU - Watanachaturaporn, Pakorn
AU - Varshney, Pramod K.
AU - Arora, Manoj K.
PY - 2005
Y1 - 2005
N2 - Remote sensing data have proven to be an attractive source for extracting accurate land cover information. For a given application, information from an individual sensor may be incomplete, inconsistent, and imprecise. Additional data sources may assist in achieving a higher degree of accuracy. Recently, support vector machines (SVM), a non-parametric algorithm, has been proposed as an alternative for classification of remote sensing data, and the results are promising. In this paper, the use of the SVM algorithm for multisource classification has been investigated. An IRS-1C LISS III image along with NDVI and DEM data layers in the Himalayan region were fused for classification. The results illustrate a significant improvement in accuracy of classification on incorporation of ancillary data over the classification performed solely on the basis of remote sensing data.
AB - Remote sensing data have proven to be an attractive source for extracting accurate land cover information. For a given application, information from an individual sensor may be incomplete, inconsistent, and imprecise. Additional data sources may assist in achieving a higher degree of accuracy. Recently, support vector machines (SVM), a non-parametric algorithm, has been proposed as an alternative for classification of remote sensing data, and the results are promising. In this paper, the use of the SVM algorithm for multisource classification has been investigated. An IRS-1C LISS III image along with NDVI and DEM data layers in the Himalayan region were fused for classification. The results illustrate a significant improvement in accuracy of classification on incorporation of ancillary data over the classification performed solely on the basis of remote sensing data.
KW - Information fusion
KW - Land cover
KW - Multisource classification
KW - Remote sensing
KW - Support vector machines
UR - http://www.scopus.com/inward/record.url?scp=33847143777&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33847143777&partnerID=8YFLogxK
U2 - 10.1109/ICIF.2005.1591911
DO - 10.1109/ICIF.2005.1591911
M3 - Conference contribution
AN - SCOPUS:33847143777
SN - 0780392868
SN - 9780780392861
T3 - 2005 7th International Conference on Information Fusion, FUSION
SP - 614
EP - 621
BT - 2005 7th International Conference on Information Fusion, FUSION
PB - IEEE Computer Society
T2 - 2005 8th International Conference on Information Fusion, FUSION
Y2 - 25 July 2005 through 28 July 2005
ER -