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<p>Monitoring shoreline variability is essential for understanding coastal dynamics and informing sustainable management and disaster risk reduction (DRR) strategies. This study analyzes long-term shoreline changes along Rushikonda and Rama Krishna (RK) Beaches, Visakhapatnam, India, from 2000 to 2023, using a synergistic approach combining satellite remote sensing and Real-Time Kinematic (RTK) GPS observations. Shoreline positions were extracted from Landsat and Sentinel-2 imagery using the Python-based CoastSat toolkit, leveraging Google Earth Engine for efficient image processing and tidal correction. CoastSat and Digital Shoreline Analysis System (DSAS) quantified spatial and temporal shoreline change rates through Weighted Linear Regression (WLR) and Net Shoreline Movement (NSM), validated against RTK-GPS data with root-mean-squared errors of 7.5&#xa0;m and 7.39&#xa0;m for Rushikonda and RK Beaches, respectively. Results reveal significant spatial variability, with Rushikonda showing moderate accretion (up to 1.4&#xa0;m/year) and localized erosion (-1.5&#xa0;m/year), while RK Beach exhibits intense erosion (-1.9&#xa0;m/year) alongside accretion (1.4&#xa0;m/year). Seasonal patterns indicate monsoon-driven erosion followed by post-monsoon recovery, identifying risk erosion zones critical for DRR. These findings support the development of early warning systems and coastal hazard mapping, enhancing disaster preparedness by delineating vulnerable areas. The integration of remote sensing and in-situ observations provides a robust framework for assessing coastal vulnerability and informing evidence-based coastal planning.</p>

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Monitoring Coastal Erosion for Disaster Risk Reduction: Synergistic Analysis of Long-Term Shoreline Variability Using Remote Sensing and RTK-GPS Observations

  • 期刊论文

  • 发表日期：

    2025年10月24日

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  • Baggu Gireesh,
  • Arun Kumar V. V. Surisetty,
  • Chintam Venkateswarlu,
  • Ramesh Madipally,
  • C. V. Naidu

摘要

Monitoring shoreline variability is essential for understanding coastal dynamics and informing sustainable management and disaster risk reduction (DRR) strategies. This study analyzes long-term shoreline changes along Rushikonda and Rama Krishna (RK) Beaches, Visakhapatnam, India, from 2000 to 2023, using a synergistic approach combining satellite remote sensing and Real-Time Kinematic (RTK) GPS observations. Shoreline positions were extracted from Landsat and Sentinel-2 imagery using the Python-based CoastSat toolkit, leveraging Google Earth Engine for efficient image processing and tidal correction. CoastSat and Digital Shoreline Analysis System (DSAS) quantified spatial and temporal shoreline change rates through Weighted Linear Regression (WLR) and Net Shoreline Movement (NSM), validated against RTK-GPS data with root-mean-squared errors of 7.5 m and 7.39 m for Rushikonda and RK Beaches, respectively. Results reveal significant spatial variability, with Rushikonda showing moderate accretion (up to 1.4 m/year) and localized erosion (-1.5 m/year), while RK Beach exhibits intense erosion (-1.9 m/year) alongside accretion (1.4 m/year). Seasonal patterns indicate monsoon-driven erosion followed by post-monsoon recovery, identifying risk erosion zones critical for DRR. These findings support the development of early warning systems and coastal hazard mapping, enhancing disaster preparedness by delineating vulnerable areas. The integration of remote sensing and in-situ observations provides a robust framework for assessing coastal vulnerability and informing evidence-based coastal planning.