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Principal Component Analysis of Building Cluster Factors

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Geo-Spatial Knowledge and Intelligence (GRMSE 2016)

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).

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Correspondence to Qiang Liu .

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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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