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Research on classification of high spatial resolution remote sensing image based on SVM

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DOI: 10.23977/geors.2021.040101 | Downloads: 5 | Views: 695

Author(s)

Hui Kong 1,2

Affiliation(s)

1 Shaanxi Provincial Land Engineering Construction Group Co., Ltd., Xi'an 710075, China; Institute of Land Engineering and Technology, Shaanxi Provincial Land Engineering Construction Group Co., Ltd., Xi'an 710021, China
2 Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Land and Resources, Xi'an 710021, China; Shaanxi Provincial Land Consolidation Engineering Technology Research Center, Xi'an 710021, China

Corresponding Author

Hui Kong

ABSTRACT

Considering the high spatial resolution remote sensing image has huge amounts of data and complex spectral distribution and the characteristics of the space characteristics of the rich, in combination with support vector machine (SVM) in tackling small sample, nonlinear and high dimensional pattern recognition problems show unique advantages, in this chapter will experiment data by using support vector machine (SVM) for high spatial resolution remote sensing image classification.

KEYWORDS

High spatial resolution, Support vector machine, Image classification, DAG method

CITE THIS PAPER

Hui Kong, Research on classification of high spatial resolution remote sensing image based on SVM . Geoscience and Remote Sensing (2021) Vol. 4: 1-6. DOI: http://dx.doi.org/10.23977/geors.2021.040101

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