Skip to main content

Web-Based Remote Sensing Image Processing Tools – A Study of Change Detection Using Landsat Imagery

  • Conference paper
Geo-Informatics in Resource Management and Sustainable Ecosystem

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

  • 3521 Accesses

Abstract

Taking advantages of web service, remote sensing image distributed processing occurs, which aims at the shortcomings of standalone solutions. In this paper, efforts have focused on interaction as well as efficiency of web-based remote sensing image change detection. The system framework consists of OGC WCS specification, Browser-Server three-tiered structure, and image change detection workflow. A pair of 4-3-2 TM bands combination images have been taken to execute an experiment. The result corresponds to actual condition.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aloisio, G., Milillo, G., Williams, R.D.: An XML architecture for high-performance web-based analysis of remote-sensing archives. Future Generation Computer Systems 16(1), 91–100 (1999)

    Article  Google Scholar 

  2. Durbha, S.S., King, R.L., Gokaraju, B., Younan, N.H.: A Proposal for the Standardization of Image Information Mining Systems via OGC Web Services Frame-work. In: International Geoscience and Remote Sensing Symposium (IGARSS), vol. 3(1), pp. III648–III651 (2008)

    Google Scholar 

  3. Guang, D., Zhenchun, H., Xianlin, Q., Xu, Z., Zengyuan, L.: Research on a Kind of Web Based Distributed Forest Remote Sensing Parallel Processing Service. In: Tan, H., Zhou, M. (eds.) CSE 2011, Part I. CCIS, vol. 201, pp. 593–600. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  4. Shen, Z., Ming, D., Li, J.: Remotely sensed image distributed processing system design with Web Services technology. In: International Geoscience and Remote Sensing Symposium (IGARSS), vol. 6, pp. 4244–4247 (2005)

    Google Scholar 

  5. Jiang, C., Geng, Z.-X., Wei, X.-F., Shen, C.: Research on networked integration technology of remote sensing image processing. In: Zhang, W., Yang, X., Xu, Z., An, P., Liu, Q., Lu, Y. (eds.) IFTC 2012. CCIS, vol. 331, pp. 1–8. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Zhao, P., Di, L.: Building a Web-Services Based Geospatial Online Analysis System. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5(6), 1780–1792 (2012)

    Article  Google Scholar 

  7. Zhao, P., Foerster, T., Yue, P.: The Geoprocessing Web. Computers and Geosciences 47, 3–12 (2012)

    Article  Google Scholar 

  8. Klaric, M.N., Claywell, B.C., Scott, G.J., Hudson, N.J., Sjahputera, O., Li, Y., Barratt, S.T., Keller, J.M., Davis, C.H.: GeoCDX: An Automated Change Detection and Exploitation System for High-Resolution Satallite Imagery. IEEE Transactions on Geoscience and Remote Sensing 51(4), 2067–2086 (2013)

    Article  Google Scholar 

  9. Landsat Project Information, http://landsat.usgs.gov

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hu, J., Meng, X. (2013). Web-Based Remote Sensing Image Processing Tools – A Study of Change Detection Using Landsat Imagery. 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_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-45025-9_42

  • 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)

Publish with us

Policies and ethics