标题：Fine spatial resolution coastline extraction from Landsat-8 OLI imagery by integrating downscaling and pansharpening approaches
作者： Wang, X (Wang, Xia); Liu, YL (Liu, Yaolin); Ling, F (Ling, Feng); Xu, SN (Xu, Shuna)
来源出版物： REMOTE SENSING LETTERS卷：9期：4 页码: 314-323 DOI：10.1080/2150704X.2017.1420928 出版年： 2018
摘要：Landsat series images are the main data resources used for coastline monitoring. However, the 30m spatial resolution of multispectral (MS) image is always dominated by mixed pixels around the coast areas. Given that the latest Landsat-8 Operational Lands Imager (OLI) imagery has a 15m panchromatic (PAN) band, it is instinctive to improve the coastline extracting accuracy by directly using the pansharpening approach. The spatial resolution of the sharpened MS image, however, may still not be sufficient in real applications, due to the meter-level spatial-temporal change of coastline. In this letter, a novel downscaling-then-pansharpening coastline extracting (DTPCE) approach is proposed to extract higher accuracy coastline from Landsat-8 OLI imagery. DTPCE first uses the radial basis function (RBF) method to downscale the 15m PAN band to a finer spatial resolution, and then produces a fine spatial resolution fused MS image by pansharpening of the downscaled PAN band and original MS bands. Finally, the fused MS image is used for coastline extracting. Comparing the extracted coastline with the reference coastline extracted from 5.8m ZiYuan-3 (ZY-3) MS image, DTPCE produced coastlines with the state-of-the-art representation in terms of both the visually and quantitatively analysis.
扩展关键词： DIFFERENCE WATER INDEX; INTERPOLATION; FEATURES; NDWI
通讯作者地址： Liu, YL (通讯作者),Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China.
[Wang, Xia; Liu, Yaolin; Xu, Shuna] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China.
[Liu, Yaolin] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan, Hubei, Peoples R China.
[Ling, Feng] Chinese Acad Sci, Inst Geodesy & Geophys, Wuhan, Hubei, Peoples R China.
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