Spatial modeling and analysis for coastal shoreline change detection across the major eastern Indian metropolises Using Earth Observation and Interpretable Machine Learning Approach

Coastal shorelines are dynamic by nature, evolving in reaction to hydro-geomorphic processes across the coast. Coastal shoreline change is accelerating globally due to shifts in land use brought on by coastal urbanisation and increasing human population pressures. In order to develop suitable risk management alternatives and ensure long-term management of populations, infrastructure, and ecosystems, coastline location over time and coastal erosion patterns are crucial for addressing current and future climate change scenarios. However, achieving this purpose is particularly challenging on sandy shores that slope gently, where even slight variations in sea level cause notable morphological changes. The coastal areas of India are both physiologically productive and highly populated. However, they are susceptible to erosion and deposition from both natural disasters and human activity. When assessing shoreline dynamics, these threats have been given priority as part of the sustainable management of coastal zones. In this study, we show how the artificial neural network (ANN), and support vector machine (SVM) algorithms can be used as interpretable machine learning (ML) models to measure changes in the shoreline. The ML model contains weights that are multiplied with relevant inputs/features to obtain a better prediction. This study showed how well Earth Observation and geographic information systems may be combined to provide comprehensive, long-term research on coastal change. According to the data, the rate of erosion along the Chennai coast varies between -0.2 and -2.5 m/year. Along the Chennai coast, accretion rates vary from 1 to 4.6 meters per year. With erosion rates ranging from -0.1 to -6.8 m/y and accretion rates ranging from 0.2 to 5.0 m/y, the shoreline of Vishakhapatnam displays a regular pattern of both processes. The accretion rate along the Puri coast varies between 0.1 and 3.22 m/y. Given how crucial these coastal towns are to India's cultural and economic endeavours, the alterations to the shorelines of these three metropolises are quite concerning.  In addition to raising sea levels globally, climate change and global warming are intensifying and increasing the frequency of extreme occurrences like tropical cyclones in the Bay of Bengal, which includes these three shores. The coasts of these urban areas may shift due to a range of human activities and natural events like tropical storms and rising sea levels. For the coastal regions of Vishakhapatnam, Puri, Chennai, and other Indian coastal towns with comparable physical attributes, this study may aid in the development of suitable management plans and regulations.