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Principal Component Analysis of Building Cluster Factors

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Geo-Spatial Knowledge and Intelligence (GRMSE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 699))

Abstract

Building properties on a map can be represented by multiple building characterization factors. In this paper, using principal component analysis method, we analyzed multiple factors characterizing buildings. Also, through dimensionality reduction transformation into a small amount of comprehensive factors, this paper proposed simplified expression of building properties, to better meet the need of map generalization for buildings.

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References

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Acknowledgments

This work was partially supported by Science Research Program of Land and Resources Department of Sichuan Province (No. KJ201613 and No. KJ20159), and The Project Supported by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources (No. KF-2016-02-007).

Author information

Authors and Affiliations

  1. Neijiang Normal University, No. 705, Dongtong Road, Neijiang, 641100, Sichuan, People’s Republic of China

    Hua Ai

  2. School of Resources and Environment, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Wust Hi-Tech Zone, Chengdu, 611731, Sichuan, People’s Republic of China

    Qiang Liu, Zhen Wang, Zezhong Zheng & Yaosen Huang

  3. Department of Land and Resources of Sichuan Province, No. 4, Baihui Road, Chengdu, 610072, Sichuan, People’s Republic of China

    Zhiqin Huang

Authors
  1. Hua Ai
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  2. Qiang Liu
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  3. Zhen Wang
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  4. Zezhong Zheng
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  5. Yaosen Huang
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  6. Zhiqin Huang
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Corresponding author

Correspondence to Qiang Liu .

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Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Wuhan University, Wuhan, China

    Fuling Bian

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Ai, H., Liu, Q., Wang, Z., Zheng, Z., Huang, Y., Huang, Z. (2017). Principal Component Analysis of Building Cluster Factors. In: Yuan, H., Geng, J., Bian, F. (eds) Geo-Spatial Knowledge and Intelligence. GRMSE 2016. Communications in Computer and Information Science, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-10-3969-0_3

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  • DOI: https://doi.org/10.1007/978-981-10-3969-0_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3968-3

  • Online ISBN: 978-981-10-3969-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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