Computational Ecology and Software (Mar 2023)
Predicting the shoreline changes in Vishakhapatnam coastal zone using Multi-output Adaptive Neuro Fuzzy Inference System
Abstract
Coastal erosion is a persistent problem occurring along the Shoreline of India. Several factors that influence the severity of erosion are community infrastructures along the coast, natural disasters, and several man-made activities. There is an increased demand for computing precise information regarding past and present trends and rates of changes in the shoreline. This research investigates the shoreline changes of the Vishakhapatnam district in Andhra Pradesh Coast, as well as finds the quantity of the erosion and accretion rate. Vishakhapatnam having a coastal length of 135 km used for the study, length of study area categorized by fours zones based on the district boundary Zone 1 - Bheemunipatnam, Zone 2 - Vishakhapatnam, Zone 3 - Anakapalli, and Zone 4 - Yellamanchili. The changes in Shoreline were computed with the help of multitemporal satellite images (Landsat 7 and Landsat 4 and 5) for the past 45 years' period, i.e., from 1974 to 2020 using Digital Shoreline Analysis System (DSAS). The rate of shoreline change was accessed using Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), End Point Rate (EPR), and Linear Regression Rate (LRR). Based on the findings the coastal maps are prepared to estimate the geological changes and shifting of shoreline position. This detailed study is found useful for exploring erosion and accretion processes in the region. About 135 km of coastline was found to be accreting in nature with an average rate of +1.13 m/yr followed by erosion of the shoreline - 0.15 m/yr. The highest and lowest SCE of about 63.4 m/yr and 75.25 m/yr were recorded in Vishakhapatnam Coast. In addition, the Multi-output Adaptive Neuro Fuzzy Inference System (MANFIS) technique is used to predict EPR, NSM, SCE, and LRR for monitoring the shoreline changes, and it could be used for further planning and development and also for disaster management authority in the decision-making process in the study area.
