Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
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Published:2023-07-31
Issue:8
Volume:11
Page:1528
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ISSN:2077-1312
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Container-title:Journal of Marine Science and Engineering
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language:en
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Short-container-title:JMSE
Author:
Dike Emmanuel Chigozie12ORCID, Oyetunji Abiodun Kolawole13ORCID, Amaechi Chiemela Victor456ORCID
Affiliation:
1. Lancaster Environment Centre (LEC), Lancaster University, Lancaster LA1 4YQ, UK 2. Department of Urban and Regional Planning, Rivers State University, Port Harcourt 500101, Nigeria 3. Department of Estate Management, University of Benin, Benin City 300287, Nigeria 4. School of Engineering, Lancaster University, Bailrigg, Lancaster LA1 4YR, UK 5. Standards Organisation of Nigeria (SON), 52 Lome Crescent, Wuse Zone 7, Abuja 900287, Nigeria 6. Institute of Energy Infrastructure, Universiti Tenaga Nasional (The National Energy University), Jalan IKRAM-UNITEN, Kajang 43000, Malaysia
Abstract
Satellite image analysis is a potentially powerful tool for monitoring coastal shoreline positions. This study explores the use of multi-temporal, dual-polarised Sentinel-1 GRD synthetic aperture radar (SAR) imagery with a spatial resolution of 10 m for delineating shorelines. It was conducted in a data-deficient and complex environment (the Niger delta of Nigeria), in a developing country with a cloud-heavy climate. The study focuses on exploring and testing the capability of using multitemporal waterlines from SAR images to derive shoreline positions at high and low tidal states. From 54 Sentinel-1 images recorded in 2017, the study selected 12 images to represent both high and low tidal states. These were spread across the wet and dry seasons in order to account for seasonal differences. Shoreline positions were obtained by identifying the land–water boundary via segmentation using histogram-minimum thresholding, vectorizing and smoothing that boundary, and averaging its position over multiple waterlines. The land–water segmentation had an overall accuracy of 95–99%. It showed differences between wet and dry season shoreline positions in areas dominated by complex creek networks, but similarities along open coasts. The SAR-derived shorelines deviated from the reference lines by a maximum of 43 m (approximately four pixels), and often less than 10 m (one pixel) in most locations (open coast, estuarine, complex creek networks) at high and low tides, except low tide lines in areas with extensive inter-tidal flats at shorelines 70 m to 370 m from the reference lines. However, for applications such as coastal vulnerability assessment, the high tide shoreline is of greater importance. Thus, depending on the application of interest, problems with low tide shoreline delineation may be irrelevant. Despite limitations, notably the relatively small number of images available that were recorded at high or low tide, the method provides a simple, objective, and cost-effective approach to monitoring shorelines at high and low tide.
Funder
Lancaster University Engineering Department Studentship Award Niger Delta Development Commission Standards Organisation of Nigeria Engineering and Physical Sciences Research Council Tertiary Education Trust Fund Universiti Tenaga Nasional (UNITEN), Malaysia
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
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