Shoreline delineation and change analysis in response to sea level rise and coastal bathymetry along the coast of Visakhapatnam, India using high-resolution optical imagery

Abstract

Coastal morphology is persistently changing in structure and environment because of natural and anthropogenic effects. Consequently, determining the spatiotemporal variability of coastal areas has become a significant source of concern. The study focuses on automatic delineation of the shoreline using edge detection algorithms; quantification of the morphological changes using a digital shoreline analysis system (DSAS); and retrieval of coastal bathymetry using linear wave dispersion relation from optical imagery for the period 2005–2020. The Canny algorithm shows efficiency in detecting shoreline precisely (95.6%). The highest erosions for net shoreline movement (NSM) are −31.71 m and −50.43 m/yr for end point rate (EPR) during 2014–2017, whereas the maximum accretions for NSM are 25.37 m and 8.64 m/yr for EPR during 2011–2014. The linear regression rate (LRR) and weighted linear regression (WLR) measure shoreline shift over a 15-year period, with the maximum rates of accretion and erosion being 1.01 m/yr and −1.02 m/yr, respectively. Shoreline prediction was carried out using the Kalman filter model for the year 2021 and was concurrently validated with field DGPS measurements. The retrieved bathymetry over the study area agrees with in situ bathymetry data with a mean bias error (MBE) of 0.39, a correlation coefficient (r) of 0.821, and a coefficient of determination (R²) of 0.742. The study also illustrates the effects of changes in mean sea level (MSL) height and coastal bathymetry on coastal morphology. Coastal bathymetry shows an inverse relationship (r = −0.765) with NSM, whereas MSL height shows a positive relationship with NSM (r = 0.403).