Abstract
Based on the spectral reflection characteristics analysis of the muddy coastline in Jiangsu, an improved spectral water index (IWI) combined with the Otsu algorithm is proposed to extract muddy coastlines from Landsat Operational Land Imager (OLI) images. The IWI-extracted coastline results are compared with those extracted by the modified normalized difference water index (MNDWI), normalized difference water index (NDWI), enhanced water index (EWI), revised normalized different water index (RNDWI) and automated water extraction index (AWEI). The results show that the IWI is not affected by tidal conditions or sand content in the water, can reduce the “salt-and-pepper” phenomenon in the Otsu algorithm classification, can accurately identify water boundaries and can extract silty mudflats and marine buildings with high accuracy. It can also significantly increase the degree of automation of coastline extraction. The IWI combined with the Otsu algorithm demonstrates high accuracy of over 84% in the extraction muddy coastline data with one-pixel tolerance, which is twice as accurate as other indices. The accuracy of extraction for all other types of coastlines is over 81%. Therefore, the IWI index combined with the Otsu algorithm is reliable for studies of sea–land processes and coastline evolutions.
Highlights
A coastline is a geomorphological signature of sea–land interactions, and has been identified by the International Geographic Information Committee (IGDC) as one of the 27 most important land surface features [1]
To better identify silty mudflats and extract coastlines under different tidal conditions, in this we study constructed a new spectral index to improve the extraction accuracy of muddy coastlines based on the analysis of spectral characteristics of nearshore features such as silty mudflats, vegetation, land and water bodies
The improved spectral water index (IWI) spectral water index constructed in this study uses the blue, green, SWIR1 and
Summary
A coastline is a geomorphological signature of sea–land interactions, and has been identified by the International Geographic Information Committee (IGDC) as one of the 27 most important land surface features [1]. To address the uncertainty in extracting water bodies or coastlines from different regions using the spectral water index, Wu et al [20] analyzed the extraction ability levels of various spectral indices for water bodies in silty shores in the Yellow River Delta and showed that the AWEInsh (one of the formulae of AWEI, the other being AWEIsh ) had the best extraction effect and that the MNDWI had a higher leakage rate for seawater than other indices. The silty mudflats, which “appear and disappear”, are the most tidally influenced areas [25,26], in which water remains after low tide, with a large number of mixed pixels of water and mudflats and complex spectral properties. The results of this study will provide a basis for the long-term monitoring of complex coastlines and a more improved understanding of sea–land processes and coastline evolution
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