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<p>Recent advancements in automated shoreline detection methods have transformed the monitoring of Ghana’s coastline dynamics. This study measures the rates of shoreline change along Ghana’s eastern coastline using the USGS Digital Shoreline Analysis System (DSAS) in conjunction with CoastSat, an automated shoreline extraction tool. This automated approach enhances efficiency, ensures consistency, and improves repeatability compared to manual extraction techniques, allowing for long-term monitoring of coastal dynamics. The study employed three statistical models including the End Point Rate (EPR) and Linear Regression Rate (LRR) to quantify shoreline change with respect to movement captured over the study period. Along with these two models, the Net Shoreline Movement (NSM) was also used to calculate the overall displacement along Ghana’s eastern coastline over a forty (40) year period with a 90% confidence interval. Based on geomorphological traits and current management techniques, the area was divided into three zones (Zone A, Zone B and Zone C), enabling a detailed comparison of the ways in which human activities and natural processes have influenced shoreline change in various coastal environments. Erosion and accretion were observed across Zone A, with the northeastern section showing the highest rates of erosion. The range of EPR values in Zone A was − 10.5&#xa0;m/year to + 10.8&#xa0;m/year, whereas the range for LRR was − 10.4&#xa0;m/year to + 12.0&#xa0;m/year. With an average distance of 15.2&#xa0;m, the NSM for Zone A demonstrated a moderate cumulative movement. In Zone B, EPR values varied from − 3.1&#xa0;m/year to + 4.1&#xa0;m/year, whereas LRR values ranged from − 1.6&#xa0;m/year to + 5.0&#xa0;m/year. During the time frame, Zone B observed a coastline movement of 20.42&#xa0;m. Zone C exhibited the most significant shoreline dynamics, with LRR values ranging from − 28.7&#xa0;m/year to + 9.7&#xa0;m/year and EPR values ranging from − 30.5&#xa0;m/year to + 8.8&#xa0;m/year. Significant shifts in the shoreline position during the research period were evidenced by the NSM values for Zone C, which displayed an average cumulative shoreline displacement of 33.5&#xa0;m. This methodology revealed significant regional diversity in shoreline dynamics, highlighting the importance of automated techniques for precise and repeatable coastal monitoring. These methods can be expanded and used in different areas, allowing coastal managers to create flexible, evidence-based plans for long-term shoreline management.</p>

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Shoreline change detection along the eastern coast of Ghana: leveraging GIS and advanced remote sensing techniques

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月26日

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  • Baah Asare-Bediako,
  • Faustina Awafu,
  • Evans Y. Boakye,
  • Emmanuel Boahen,
  • Cyril D. Boateng,
  • David D. Wemegah,
  • Akyana Britwum,
  • Michael K. E. Donkor,
  • Jeffrey N. A. Aryee,
  • Emmanuel K. Brempong,
  • Leonard K. Amekudzi

摘要

Recent advancements in automated shoreline detection methods have transformed the monitoring of Ghana’s coastline dynamics. This study measures the rates of shoreline change along Ghana’s eastern coastline using the USGS Digital Shoreline Analysis System (DSAS) in conjunction with CoastSat, an automated shoreline extraction tool. This automated approach enhances efficiency, ensures consistency, and improves repeatability compared to manual extraction techniques, allowing for long-term monitoring of coastal dynamics. The study employed three statistical models including the End Point Rate (EPR) and Linear Regression Rate (LRR) to quantify shoreline change with respect to movement captured over the study period. Along with these two models, the Net Shoreline Movement (NSM) was also used to calculate the overall displacement along Ghana’s eastern coastline over a forty (40) year period with a 90% confidence interval. Based on geomorphological traits and current management techniques, the area was divided into three zones (Zone A, Zone B and Zone C), enabling a detailed comparison of the ways in which human activities and natural processes have influenced shoreline change in various coastal environments. Erosion and accretion were observed across Zone A, with the northeastern section showing the highest rates of erosion. The range of EPR values in Zone A was − 10.5 m/year to + 10.8 m/year, whereas the range for LRR was − 10.4 m/year to + 12.0 m/year. With an average distance of 15.2 m, the NSM for Zone A demonstrated a moderate cumulative movement. In Zone B, EPR values varied from − 3.1 m/year to + 4.1 m/year, whereas LRR values ranged from − 1.6 m/year to + 5.0 m/year. During the time frame, Zone B observed a coastline movement of 20.42 m. Zone C exhibited the most significant shoreline dynamics, with LRR values ranging from − 28.7 m/year to + 9.7 m/year and EPR values ranging from − 30.5 m/year to + 8.8 m/year. Significant shifts in the shoreline position during the research period were evidenced by the NSM values for Zone C, which displayed an average cumulative shoreline displacement of 33.5 m. This methodology revealed significant regional diversity in shoreline dynamics, highlighting the importance of automated techniques for precise and repeatable coastal monitoring. These methods can be expanded and used in different areas, allowing coastal managers to create flexible, evidence-based plans for long-term shoreline management.