A nonparametric fuzzy shoreline extraction approach from Sentinel-1A by integration of RASAT pan-sharpened imagery

Nusret Demir*, Bülent Bayram, Dursun Zafer Şeker, Selen Oy, Fırat Erdem

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Coastal zones are among the most important features of the earth as they have social and economic importance for the environment. Thus, they should be frequently monitored for management issues, for example, shoreline erosion, and any essential precautions for safe management taken. Shoreline extraction is an important tool to determine coastal changes. Modern technologies such as remote sensing give an opportunity to gain up-to-date, accurate, and reliable information with fast data acquisition for coastal regions. In this study, two different coastal areas, one in the northern part of Turkey (Terkos/Istanbul) and the second from the southern part of the country (Kemer/Antalya), were studied. The main objective of this study is to extract shorelines from Sentinel-1A radio detection and ranging satellite data using a non-parametric fuzzy approach, by exploiting Turkish multispectral RASAT satellite images. For this purpose, a whale optimization algorithm was initially employed to create land and water classes from RASAT images. The created classes were used as inputs to determine fuzzy membership values for non-parametric shoreline extractions from Sentinel-1A images. The results are evaluated in comparison with manually digitized reference shorelines by calculating the perpendicular distances between the digitized and remotely sensed shorelines. The calculated average distances from the RASAT-integrated Sentinel-1A (RASAT + Sentinel-1A) for Terkos/Istanbul and Kemer/Antalya were 29.18 m and 16.78 m, respectively. Average differences were also calculated using only RASAT images as 13.37 m and 6.29 m for both areas, respectively.

Original languageEnglish
Pages (from-to)401-415
Number of pages15
JournalGeo-Marine Letters
Volume39
Issue number5
DOIs
Publication statusPublished - 1 Oct 2019

Bibliographical note

Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Funding

This study received support from TUBITAK (The Scientific and Technological Research Council of Turkey) with project number 115Y718. The authors acknowledge the support of Prof. Dr. Mustafa ?zdemir (Akdeniz University, Dept. of Mathematics) for the notation of fuzzy operations, and Assoc. Prof. Dr. Bekir Taner San (Akdeniz University, Dept. of Geological Engineering, for the sources of the coastal geology.

FundersFunder number
TUBITAK
The Scientific and Technological Research Council of Turkey115Y718
Akdeniz Üniversitesi

    Keywords

    • Fuzzy image segmentation
    • RASAT
    • Remote sensing
    • Sentinel-1A SAR
    • Whale optimization

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