Extraction of shorelines using satellite imagery is an eAective method because customary digitization is a long and hectic process. This study focuses on extracting and detecting shoreline changes from Landsat-8 imageries of the Visakhapatnam-Kakinada coast along the east coast of India using an object-based approach. An objectbased approach for the automatic detection of coastline from Landsat imagery using the Feature Extraction WorkCow by Maximum Likelihood is implemented by the maximum classiBcation method (MLC). The resulting vector polyline is smoothened for every 100 m using ArcGIS software. Delineation of multi-temporal satellite images was performed by visual interpretation from 2014 to 2019 to detect the shoreline changes. Different available techniques and methods are employed to observe shoreline changes. In addition to this, the shoreline information simulated by satellite remote sensing is in fair agreement with RTK GPS observations. The observed and remote sensing shoreline changes help to identify the areas of accretion and eroding zones over the long term. During this study, erosion and deposition changes were observed along RK beach, Rushikonda beach, Uppada beach, and Kakinada beach. The spatial variation rates were calculated using the statistical methods of the Digital Shoreline Analysis System (DSAS) during speciBc periods. The maximum observed shoreline accretion and erosion rates at Kakinada are 5.3 and -4.35 m/year indicates slight accretion. The maximum observed accretion and erosion rates at Uppada beach are 3.8 and -6.78 m/year, respectively indicating erosion. Similarly, atRKBeach the maximum observed shoreline accretion and erosion rates are 3.68 and -3.68 m/year, respectively indicating the beach is in a stable state. At Rushikonda beach, the maximum observed shoreline accretion and erosion rates are 2.24 and -3.04 m/year, respectively indicating erosion.