Study on Optimal Segmenting Scale of Grassland in Remote Sensing Objects

Wei Cui; Qing Qing Li

doi:10.4028/www.scientific.net/AMR.171-172.240

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 171-172Study on Optimal Segmenting Scale of Grassland in...

Study on Optimal Segmenting Scale of Grassland in Remote Sensing Objects

Abstract:

Determining optimal segmenting scale of remote sensing objects is very important for remote sensing classification and identification. At present, selecting the optimal scales for objects in remote sensing images usually uses two methods, that is, average local variance and maximum area. Due to influences of subjective factors and difficult to implement, this paper proposes a new method based on fractal dimension to solve this problem. This experiment probes certain internal connections between fractal dimension on different scale and optimal segmenting scale of remote sensing objects. It offers a new method for seeking efficient ways to determine optimal scales of different objects in remote sensing images

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Periodical:

Advanced Materials Research (Volumes 171-172)

Pages:

240-245

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.171-172.240

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Online since:

December 2010

Authors:

Wei Cui, Qing Qing Li

Keywords:

Fractal Dimension, Object-Oriented (OO), Optimal Scale, Remote Sensing

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References

[1] Benz U C , Peter H , Gregor W , et al. Multi-resolution , Object-oriented Fuzzy Analysis of Remote Sensing Data for GIS2ready Information [J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2004 (58): 239-258.

DOI: 10.1016/j.isprsjprs.2003.10.002

Google Scholar

[2] Definiens Image GmbH. eCogniton User Guide [M]. German, 2007: 26-27, 207-217.

Google Scholar

[3] WondcocK C E, Strahler A H. The factor of scale in remote sensing [J]. Remote Sensing of Environment, 1987, 21(3): 311-332.

DOI: 10.1016/0034-4257(87)90015-0

Google Scholar

[4] Huang HuiPing. Seale issues in object-oriented image analysis [D]. Beijing: Institute of Remote Sensing Applications, Chinese Academy of Sciences, (2003).

Google Scholar

[5] Mandelbrot B B. How long is the coast of Britain Statistical self-similarity and fractional dimension. Science，1967，156(3775): 636-638.

DOI: 10.1126/science.156.3775.636

Google Scholar

[6] LIU Xiao-hui. Application of Fractal Dimension Model for Land Use Study. Scientia Geographica Sinica, (2008).

Google Scholar

[7] BAI Weiguo. The Methods Research in Analyzing Spatial Change in the Region of Alpine Grassland Ecosystem [D]. PhD thesis, Beijing Forestry University, (2004).

Google Scholar

[8] Li Hou-qiang. Some Open Questions for Fractal Investigations. Nature Magazine, 1994, 17(2): 103-105.

Google Scholar