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Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) pp 71–78Cite as

Hybrid Landscape Change Detection Methods in a Noisy Data Environment

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 520))

Abstract

The most used in practice land cover change detection methods by remote sensing data are considered. The approaches to the hybrid methods development those involve different methods of combining procedures and results are proposed. The results of change detection methods in different noisy data environment and intensities are presented. It is shown that an application of the hybrid methods for the change detection by data with different characteristics and noises is one of the most promising approaches to the land cover change detection, not only increasing the robustness of the results, but also simplifying the automated solution of this problem.

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Acknowledgements

This work was supported by Russian Foundation for Basic Research (grant 14-07-00027a).

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Authors and Affiliations

  1. National Research Tomsk Polytechnic University, Institute of Cybernetics, Lenin Avenue 30, 634050, Tomsk, Russia

    Anton Afanasyev

  2. Computer Science Department, National Research Tomsk State University, Lenin Avenue 36, 634050, Tomsk, Russia

    Alexander Zamyatin

Authors
  1. Anton Afanasyev
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  2. Alexander Zamyatin
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Corresponding author

Correspondence to Anton Afanasyev .

Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia

    Mohamed Othman

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  4. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  5. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Hairulnizam Mahdin

  6. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

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Afanasyev, A., Zamyatin, A. (2019). Hybrid Landscape Change Detection Methods in a Noisy Data Environment. In: Abawajy, J., Othman, M., Ghazali, R., Deris, M., Mahdin, H., Herawan, T. (eds) Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) . Lecture Notes in Electrical Engineering, vol 520. Springer, Singapore. https://doi.org/10.1007/978-981-13-1799-6_8

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