Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region

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...

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Main Authors: Dike E.C., Oyetunji A.K., Amaechi C.V.
Other Authors: 57194337934
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Published: Multidisciplinary Digital Publishing Institute (MDPI) 2024
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spelling my.uniten.dspace-340832024-10-14T11:17:54Z Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region Dike E.C. Oyetunji A.K. Amaechi C.V. 57194337934 57192178716 57204818354 backscatter coastal data Niger Delta positional accuracy shoreline delineation synthetic aperture radar (SAR) thresholding vectorizing 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. � 2023 by the authors. Final 2024-10-14T03:17:54Z 2024-10-14T03:17:54Z 2023 Article 10.3390/jmse11081528 2-s2.0-85168874963 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168874963&doi=10.3390%2fjmse11081528&partnerID=40&md5=c59a6c474ec814533e51c4bbf9034464 https://irepository.uniten.edu.my/handle/123456789/34083 11 8 1528 All Open Access Gold Open Access Multidisciplinary Digital Publishing Institute (MDPI) Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic backscatter
coastal data
Niger Delta
positional accuracy
shoreline delineation
synthetic aperture radar (SAR)
thresholding
vectorizing
spellingShingle backscatter
coastal data
Niger Delta
positional accuracy
shoreline delineation
synthetic aperture radar (SAR)
thresholding
vectorizing
Dike E.C.
Oyetunji A.K.
Amaechi C.V.
Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
description 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. � 2023 by the authors.
author2 57194337934
author_facet 57194337934
Dike E.C.
Oyetunji A.K.
Amaechi C.V.
format Article
author Dike E.C.
Oyetunji A.K.
Amaechi C.V.
author_sort Dike E.C.
title Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
title_short Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
title_full Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
title_fullStr Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
title_full_unstemmed Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region
title_sort shoreline delineation from synthetic aperture radar (sar) imagery for high and low tidal states in data-deficient niger delta region
publisher Multidisciplinary Digital Publishing Institute (MDPI)
publishDate 2024
_version_ 1814061165172490240
score 13.214268