| Technology and Methodology |
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Extraction of Nitaria tangutorum dune in Minqin County based on GF-2 data |
| HUA Yongchun1, LI Zengyuan1, GAO Zhihai1, GUO Zhong2 |
1. Research Institute of Resource Information, Chinese Academy of Forestry, Beijing 100091, China;
2. Inner Mongolia Academy of Forestry Science, Hohhot 010010, China |
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Abstract In this paper, the authors used GF-2 remote sensing data to extract Nitaria tangutorum dune in Minqin County. The authors made full use of the minimum/maximum difference texture information and length-width ratio as well as area of geometric features of Nitaria tangutorum dune, by using multiresolution segmentation, object-oriented classification and threshold extraction methods, made quantitative extraction of the Nitaria tangutorum dune. The results show that the spatial position accuracy of Nitaria tangutorum dune can reach 94%, which could completely meet the requirement of the research. Compared with the actual area of Nitaria tangutorum dune, the linear regression R2 can reach 0.77, the standard deviation is 5.77, but the area extraction accuracy remains unsatisfactory, which needs further improvement.
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| Keywords
big data
remote sensing data
management and service
spatial analysis
geographic national conditions monitoring
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Issue Date: 23 January 2017
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2017,
Vol. 29
