Forecasting coastal stability: Digital shoreline analysis system and machine learning techniques in evaluating Impacts of cyclones

Abstract

The eastern and western shores of India are affected by tropical cyclones, which lead to serious socio-environmental issues. This study analyzed shoreline changes caused by cyclone Gaja and Michaung in South eastern coastal zone of India. The goal of this study is to evaluate shoreline change rates at two significant Indian regions that are frequently hit by cyclones. Two significant cyclones, the Gaja cyclone in Tamilnadu and the Michaung cyclone in Andhra Pradesh, defined the study regions. Multi-temporal satellite imagery and an ArcGIS-based DSAS model program were employed to detect and quantify changes along the coastline, focusing on erosion and sedimentation dynamics. The study, in conjunction with shoreline accretion and erosion patterns, analyzed three decades (1993, 2003, 2013, and 2023) of Landsat images. It employed three DSAS statistical models: Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR). The software automatically computes confidence intervals, typically at the 95 % level, for each rate of change. Accretion and erosion occur along the shoreline at different rates, according to these data. The average rate of accretion is approximately + 9 m/year along the Kodiyakarai area and + 28 m/year along Elachetladibba. The highest erosion rate is approximately −16 m/year in the Kodiyakarai coastal zone and −25 m/year in the Diviseema coastal zone.