Skip to main content
SpringerLink
Log in

Optimum segmentation of simple objects in high-resolution remote sensing imagery in coastal areas

  • Published:
Science in China Series D: Earth Sciences Aims and scope Submit manuscript

Abstract

The optimum segmentation of ground objects in a landscape is essential for interpretation of high-resolution remotely sensed imagery and detection of objects; and it is also a technical foundation to efficiently use spatial information in remote sensing imagery. Landscapes are complex system composed of a large number of heterogeneous components. There are many explicit homogeneous image objects that have similar spectral character and yet differ from surrounding objects in high-resolution remote sensing imagery. Thereby, a new concept of Distinctive Feature of fractal is put forward and used in deriving Distinctive Feature curve of fractal evolution in multiscale segmentation. Through distinguishing the extremum condition of Distinctive Feature curve and the inclusion relationship of fractals in multiscale representation the Scalar Order is built. This can help to determinate the optimum scale in image segmentation for simple-objects, and the potential meaningful image-object fitting the intrinsic scale of the dominant landscape object can be obtained. Based on the application in high-resolution remote sensing imagery in coastal areas, a satisfactory result was acquired.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Green E P, Mumby P J, Edwards A J, et al. A review of remote sensing for the assessment and management of tropical coastal resources. Coastal Management, 1996, 24: 1–40

    Google Scholar 

  2. Phinn S R, Menges C, Hill G T E, et al. Optimizing remotely sensed solutions for monitoring, modeling, and managing coastal environments. Remote Sensing Environ, 2000, 73(2): 117–132

    Article  Google Scholar 

  3. Slater J, Brown R. Changing landscapes: monitoring environmentally sensitive area using satellite imagery. Int J Remote Sens, 2000, 21: 2753–2767

    Article  Google Scholar 

  4. Weng Q. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modeling. J Environ Manage, 2002, 64: 273–284

    Article  Google Scholar 

  5. Ozesmi S L, Bauer M E. Satellite remote sensing of wetland. Wetland Ecol Manage, 2002, 10: 381–402

    Article  Google Scholar 

  6. Mumby P J, Edwards A J. Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy. Remote Sensing Environ, 2000, 82: 248–257

    Article  Google Scholar 

  7. Wang L, Sousa W, Gong P, et al. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sensing Environ, 2004, 91: 432–440

    Article  Google Scholar 

  8. Quattrochi D A, Goodchild M F. Scale in Remote Sensing and GIS. Ration: Lewis Publishers, 1997

    Google Scholar 

  9. Blaschke T, Lang S, Lorup E, et al. Object-oriented image processing in an integrated GIS/remote sensing environment and perspectives for environmental applications. In: Cremers A, Greve K, (Hrsg.): Umweltinformation für Planung, Politik und Öffentlichkeit/Environmental Information for Planning, Politics and the Public, Metropolis Verlag, Marburg, 2000. 555–570

    Google Scholar 

  10. Canny J. A computational approach to edge detection. IEEE Trans Pattern Analy Mach Inte, 1986, 8: 679–697.

    Article  Google Scholar 

  11. Gorte B. Probabilistic Segmentation of Remotely Sensed Images, In: ITC Publication Series, 1998, No. 63

  12. Lindeberg T. Scale-Space Theory in Computer Vision. Dordrecht: Kluwer Academic Publishing, 1994. 423

    Google Scholar 

  13. Ghassemian H, Landgrebe D A. Object-oriented feature extraction method for image data compaction. IEEE Control Systems Magazine. 1988, 8(3): 42–48

    Article  Google Scholar 

  14. Baatz M, Shäpe A. Object-oriented and multi-scale image analysis in semantic networks. In: Proc. of the 2nd International Symposium on Operationalization of Remote Sensing August 16th–20th, Enschede, ITC, 1999

  15. Baatz M, Shäpe A. Multiresolution segmentation, an optimization approach for high quality multi-scale image segmentation. In: Strobl T, Blaschke T, Griesebner G, eds. Angewandte Geographische informationsverarbeitung, XII. Beitrage zum AGIT-Symposium Salzburg 2000, Karlsruhe: Wichmann H, Verlag, 2000. 12–23

    Google Scholar 

  16. Hay G J, Blaschke T, Marceau D J, et al. A comparison of three image-object methods for the multiscale analysis of landscape structure. J Photogramm Remote Sens, 2003, 1253: 1–19

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou, 310012, China

    Chen Jianyu, Pan Delu & Mao Zhihua

  2. Shanghai Institute of Technical Physics, Chinese Academy of Science, Shanghai, 200083, China

    Chen Jianyu

Authors
  1. Chen Jianyu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pan Delu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mao Zhihua
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chen Jianyu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, J., Pan, D. & Mao, Z. Optimum segmentation of simple objects in high-resolution remote sensing imagery in coastal areas. SCI CHINA SER D 49, 1195–1203 (2006). https://doi.org/10.1007/s11430-006-2005-x

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-006-2005-x

Keywords

Search

Navigation