Coastline Detection with Gaofen-3 SAR Images Using an Improved FCM Method.

Meng An,Qian Sun,Jun Hu,Ziwei Zhu,Yuqi Tang

doi:10.3390/s18061898

Meng An, Qian Sun + Show 3 more

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https://doi.org/10.3390/s18061898

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Abstract

The coastline detection is one of the main applications of the Gaofen-3 satellite in the ocean field. However, the capability of Gaofen-3 SAR image in coastline detection has not yet been validated. In this paper, two Gaofen-3 SAR images, acquired in 2016, were used to extract the coastlines of the regions of Bohai and Taihu in China, respectively. The classical Fuzzy C-means (FCM) method was used in the coastline detection, but had been improved by combining the Wavelet decomposition algorithm to better suppress the inherent speckle noises of SAR image. Coastline detection results obtained from two Sentinel-1 SAR images acquired on the same regions were compared with those of the Gaofen-3 images. By using the manually delineated coastlines as the standards in the qualitative evaluations, improvements of about 12.0%, 8.3%, 23.8%, and 9.4% can be achieved by the improved FCM method with respect to the indicators of mean, RMSE, PGSD, and P90%, respectively; demonstrating that the Gaofen-3 data is superior to the Sentinel-1 data in the detection of coastline.

Highlights

A coastline is the continuous boundary between land and ocean masses
The performance of the Gaofen-3 synthetic aperture radar (SAR) data on the coastline detection was examined over the Bohai and Taihu regions in China
The results showed that the improved Fuzzy C-means (FCM) method can better suppress the noise interferences in the Gaofen-3 images than the original FCM method

Summary

Introduction

A coastline is the continuous boundary between land and ocean masses. It is the baseline for dividing the administrative area of the ocean and the land, and serves as the dividing line between the ocean depth datum and the land elevation datum. Monitoring the dynamic change of coastline is of great significance for the ocean management [1,2,3,4]. Field measurements (e.g., GPS and total station) are the traditional methods for coastline detection. Optical remote sensing provides a fast and effective method for detecting dynamic changes of coastline [5]. Coastline detection from synthetic aperture radar (SAR) image has had faster growing development due to its wide spatial coverage, high resolution, strong penetration ability, and all-day/all-weather imaging capabilities [6]

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