Arshid Hussain Malik Randhi Uma Devi


Coastlines have been subject to ongoing vulnerability from natural disasters, resulting in erosion and accretion occurring at varying intervals. The impacts of human activities and alterations in natural processes, including those induced by climate change, exacerbate the existing challenges faced along coastal regions. The present study aimed to analyze the changing shoreline along the Bapatla coastal tract in the upper coromandel coast of Andhra Pradesh due to erosion and accretion using the DSAS toolbar in ArcGIS software. Multiple statistical methods are available in DSAS; the present study confined  attention to the end point rate (EPR), linear regression rate (LRR), and net shoreline movement (NSM) for this investigation. The Nizampatnam Mandal had the greatest erosion rate (-16.8 m/yr) and accretion rate (10.5 m/yr), according to EPR, as well as the highest erosion rate (-16.7 m/yr) and accretion rate (10.4 m/yr) according to LRR. As per NSM, between 1990 and 2020, the highest erosion and accretion was seen again in Nizampatnam. The shoreline at Nizampatnam either retreated by as much as -285.2 meters or advanced by 211.1 meters. The research indicated that the Bapatla district's shoreline is susceptible to erosion and accretion.   The present investigation revealed that the coastal region of Bapatla district exhibits susceptibility to both erosion and accretion phenomena. The findings of the present study hold significant implications for professionals in the fields of coastal science, engineering, and administration. The findings are of utmost importance in the development of sustainable approaches for coastal management. 





Bapatla District, Digital Shoreline Analysis System DSAS, Erosion and Accretion, Geographic Information System (GIS), Remote Sensing (RS), Shoreline change

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Research Articles

How to Cite

Analysis of shoreline changes in the severe storm surge region of upper Coromandel coast, India, using Remote sensing (RS) and Geographic information system (GIS). (2023). Journal of Applied and Natural Science, 15(4), 1453-1466. https://doi.org/10.31018/jans.v15i4.5074