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Research of Regional Real Estate Early Warning Based on Spatial Regression

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Geo-Informatics in Resource Management and Sustainable Ecosystem

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 398))

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Abstract

It is importantthatspatial statistical analysis is used into forecasting trends of the real estate market. In this paper, we select 740 living areas in Jinan, Shandong Province for Hot-Spot analysis. Then we use Moran’s I spatial autocorrelation analysis to determine spatial association for each cell. Finally spatial regression method is used to predict real estate trends in Jinan. The results present that the northwestern region show slow development, and the southeastern region show rapid development.

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References

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Author information

Authors and Affiliations

  1. School of Civil Engineering and Architecture, University of Jinan, Jinan, 250022, China

    Jun Zhao, Qiqing Duan & Zhifang Xi

Authors
  1. Jun Zhao
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  2. Qiqing Duan
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  3. Zhifang Xi
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Editor information

Editors and Affiliations

  1. Wuhan University, No. 37, Luoyu Road, 430079, Wuhan, Hubei, China

    Fuling Bian

  2. Institute for Geospatial Research and Education, Michigan University, 125 King Hall, 48197, Ypsilanti, MI, USA

    Yichun Xie

  3. Wuhan University, No 37 Luoyu Road, 430079, Wuhan, Hubei, China

    Xiaohui Cui  & Yixin Zeng  & 

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Zhao, J., Duan, Q., Xi, Z. (2013). Research of Regional Real Estate Early Warning Based on Spatial Regression. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. Communications in Computer and Information Science, vol 398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45025-9_9

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  • DOI: https://doi.org/10.1007/978-3-642-45025-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45024-2

  • Online ISBN: 978-3-642-45025-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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