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Proceedings Paper

Zoning types of mountain forest restoration in the upper Min River supported by image auto-recognition system
Author(s): Q. Wang; F. C. Li
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Paper Abstract

Image auto- recognition system is a processing platform for extracting the grid data of characteristic element from original map and converting grid data to vector data. Selecting five maps about precipitation, evaporation, vegetation, soil erosion, and human activities, this paper applied images auto- recognition system and GIS technique to define and distinguish the boundary between natural restoration, human reconstruction and arid zone in the Upper Reaches of Min River. The results show that: images auto-recognition system efficiently extracted the grid data of characteristic element from original landscape patterns, and converted the grid data to vector data accurately.

Paper Details

Date Published: 9 July 2011
PDF: 6 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 800914 (9 July 2011); doi: 10.1117/12.896501
Show Author Affiliations
Q. Wang, Southwest Univ. of Science and Technology (China)
F. C. Li, Institute of Mountain Hazards and Environment (China)
Graduate School of the Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)

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