Skip to main content

Analysis of Shanghai Urban Expansion Based on Multi-temporal Remote Sensing Images

  • Conference paper
  • First Online:
Sustainable Development of Water and Environment (ICSDWE 2019)

Part of the book series: Environmental Science and Engineering ((ENVSCIENCE))

  • 612 Accesses

Abstract

Being different from the traditional analysis of urban expansion in Shanghai from the perspective of humanities or urban geography, this study applies the Remote Sensing (RS) and Geographical Information System (GIS) spatial information technologies to analyze the spatio-temporal characteristics and evolution of urban land expansion in Shanghai’s urbanization process. It provides a basis for further research on the mechanism of urbanization process. In this study, we processed and analyzed the multi-temporal remote sensing images (Landsat series) in Shanghai from 1995 to 2016. A multidimensional feature space was constructed. Then the image classification was carried out by the support vector machine (SVM). On the basis of classification results, the central city zone was extracted by method of regional connectivity. After analyzing the change of area, center of gravity, location and spatial distribution of the central city zone, the spatial layout and trend of urban expansion are obtained. Finally, the driving force of urban expansion in Shanghai is analyzed. The analysis results accurately reflect the process of Shanghai’s urban expansion .

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Chen Z, Chen J (2006) Urban land image recognition analysis and mapping based on NDBI index method. Geo-inf Sci 8(2):137–140

    Google Scholar 

  • Han-qiu X (2005) Research on water information extraction by using improved normalized difference water body index (MNDWI). J Remote Sens 9(5):590–595

    Google Scholar 

  • Huang C, Davis LS, Townshend J (2002) An assessment of support vector machines for land cover classification. Int J Remote Sens 23(4):725–749

    Article  Google Scholar 

  • Huete AR (1988) A soil-adjusted vegetation index(SAVI). Remote Sens Environ 25(3):295

    Article  Google Scholar 

  • Kantakumar LN, Kumar S, Schneider K (2016) Spatiotemporal urban expansion in Pune metropolis India using remote sensing. Habitat Int 51:11–22

    Article  Google Scholar 

  • Li A, Liu S, Lü A (2011) Research on expansion of built-up area in Zhengzhou during 1999 2007 based on multi-original remote sensing images. J Zhengzhou University 32(2):125–128

    CAS  Google Scholar 

  • Tan W, Liu B, zhang Z et al (2009) Remote sensing monitoring and analysis of the built-up area of Kunming city in the past three decades. Geo-Inf Sci 11(01):117–124

    Google Scholar 

  • Thompson WD, Walter SD (1988) A reappraisal of the kappa coefficient. J Clin Epidemiol 41(10):949

    Article  CAS  Google Scholar 

  • Xu L (2010) Analysis of the impact of Shanghai world expo 2010 on Shanghai urban economy. Market Weekly Heoretical Res (5):28–30

    Google Scholar 

  • Shanghai statistics bureau. Shanghai statistical book [Z]. Statistical Press, Beijing, China

    Google Scholar 

  • Zhang Z, Jia D et al (2013) Quantitative analysis of urban spatial morphology and characteristics—a case study of the main urban area of chongqing. Geo-Inf Sci 15(2):297–306

    Google Scholar 

  • Zhan Xin, Pan Wen-bin, et al (2017) Research of urban expansion measures based on multi-source remote sensing data-a case study of Xiamen City. J Fuzhou Univ (Natural Science Edition) 45:355–361

    Google Scholar 

Download references

Acknowledgements

This study has been supported by the National Science Foundation of China (41771449).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jie Yu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lin, Y., Hu, Y., Yu, J. (2019). Analysis of Shanghai Urban Expansion Based on Multi-temporal Remote Sensing Images. In: Sun, R., Fei, L. (eds) Sustainable Development of Water and Environment. ICSDWE 2019. Environmental Science and Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-030-16729-5_5

Download citation

Publish with us

Policies and ethics