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Qiao Xuejin, Wang Qing, Zhan Chao, Wang Xin, Wang Hongyan, Du Guoyun, Li Xueyan. Study on automatic extraction of coastline in the Yellow River Delta based on multi-spectral data[J]. Haiyang Xuebao, 2016, 38(7): 59-71. doi: 10.3969/j.issn.0253-4193.2016.07.006
Citation: Qiao Xuejin, Wang Qing, Zhan Chao, Wang Xin, Wang Hongyan, Du Guoyun, Li Xueyan. Study on automatic extraction of coastline in the Yellow River Delta based on multi-spectral data[J]. Haiyang Xuebao, 2016, 38(7): 59-71. doi: 10.3969/j.issn.0253-4193.2016.07.006

Study on automatic extraction of coastline in the Yellow River Delta based on multi-spectral data

doi: 10.3969/j.issn.0253-4193.2016.07.006
  • Received Date: 2015-11-29
  • The automatic extraction of coastline based on multi-spectral data has been an important question which has received attention for a long time. In this paper, aiming at the situation of the coastline extraction with a relatively single method based on either the spectral characteristic or the spatial relation, the authors present an automatic extraction method which concludes both spectral characteristics and spatial relations. Firstly, through comparing the measured spectrums with the Landsat8-OLI image of 2014 and choosing sensitive bands to build extraction model, we classified and extracted the coastline of the Yellow River Delta. Secondly, through using the method of visual interpretation, we extracted the coastline of experimental coastal section based on the coastline revision of Shandong Province in the 908 special project. Thirdly, through using the ROC (Receiver Operating Characteristic) curve, we evaluated the accuracy of the extraction result by 0.5 pixels and 1 pixel individually. Finally, the experimental result of vector-based coastline was directly applied in the subsequent GIS analysis. On the whole, through this new method, we can extract the coastline of Yellow River Delta quickly with an accuracy of one pixel and an extraction confidence level of higher than 90%.

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