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Zoning types of mountain forest restoration in the upper min river supported by image auto-recognition system
Language英语
Wang, Q.1; Zou, Q.2,3; Li, F.C.2,3; Mu, C.L.4; Yu, Y.1; Ma, X.1; Jiang, Y.J.1; Lu, H.1
2011
Source PublicationProceedings of SPIE - The International Society for Optical Engineering
Author of SourceSPIE
Volume8009
Pages800914
meetingThird International Conference on Digital Image Processing, ICDIP 2011
Conference Date2011-4-15
Conference PlaceChengdu
CountryChina
Contribution Rank2
AbstractImage auto- recognition system is a processing platform for extracting the grid data ofcharacteristic 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 imagesauto- recognition system and GIS technique to define and distinguish the boundary between naturalrestoration, 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. 
Keywordcomponent images auto-recognition system forest restoration the Upper Reaches of Min River, Zoning, GIS map element vectorization
DOI10.1117/12.896501
ISBN9780819485830
ISSN0277786X
Indexed ByEI
Accession numberAccession number:;20113114196292
Citation statistics
Document Type会议论文
Identifierhttp://ir.imde.ac.cn/handle/131551/25941
Collection山区发展研究中心
Affiliation1.School of Environment and Resource, Southwest University of Science and Technology, Mianyang, Sichuan Province, China;
2.Institute of Mountain Hazards and Environment, CAS, Chengdu, Sichuan Province, China;
3.Graduate School, Chinese Academy of Sciences, Beijing, China;
4.Sichuan Academy of Forestry, Chengdu, Sichuan Province, China
Recommended Citation
GB/T 7714
Wang, Q.,Zou, Q.,Li, F.C.,et al. Zoning types of mountain forest restoration in the upper min river supported by image auto-recognition system[C]//SPIE,2011:800914.
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