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International Conference on Machine Learning for Cyber Security

ML4CS 2020: Machine Learning for Cyber Security pp 48–54Cite as

A Classification Method of Land Cover Based on Support Vector Machines

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12488))

Abstract

In this paper, we develop a classification method of land cover based on support vector machines. As a case study, we choose five Landsat images to retrieve land cover maps in Shenzhen, China from 1979 to 2005. The classification method is based on support vector machines with assistance from visual interpretation. And then we take use of the complex network approach to analyze the character of land use-cover change from an overall perspective. The result shows that the main changes of land use-cover are different over time. The medium of bare land during the urban construction can hardly be witnessed, even though the time intervals are shorter than the two periods before. It reveals the transformation from vegetation to urban becomes faster. The transformation from vegetation to bare land is hard to be witnessed in the late stage. As bare land is the medium for transforming vegetation to urban land in Shenzhen during the past years from 1979 to 2005.

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Acknowledgments

This work was supported in part by the Basic and Applied Basic Research Funding Program of Guangdong Province of China (Grant No. 2019A1515110303), the Natural Science Foundation of Guangdong Province (Grant No. 2018A030313014), the research team project of Dongguan University of Technology (Grant No. TDY-B2019009), the Guangdong University Key Project (2019KZDXM012).

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Authors and Affiliations

  1. School of Computer Science and Technology, Dongguan University of Technology, Dongguan, 523808, People’s Republic of China

    Kai Ding, Ming Tao, Huijuan Xiao & Peican Huang

  2. Department of Urban Spatial Smart Sensing, Shenzhen University, Shenzhen, 518060, People’s Republic of China

    Chisheng Wang & Chao Yang

Authors
  1. Kai Ding
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  2. Chisheng Wang
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  3. Ming Tao
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  4. Huijuan Xiao
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  5. Chao Yang
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  6. Peican Huang
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Corresponding author

Correspondence to Chisheng Wang .

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Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Ding, K., Wang, C., Tao, M., Xiao, H., Yang, C., Huang, P. (2020). A Classification Method of Land Cover Based on Support Vector Machines. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_5

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  • DOI: https://doi.org/10.1007/978-3-030-62463-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62462-0

  • Online ISBN: 978-3-030-62463-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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