Assessment and prediction of shoreline change using multi-temporal satellite data and geostatistics: A case study on the eastern coast of India

Abstract

Climate change and rising sea level is transforming global coastlines as corroborated by significant changes in the position of shoreline witnessed through coastal erosion or accretion. Andhra Pradesh has the second longest (972 km) coastline in India. The present study analyzed shoreline change and its future prediction by employing satellite-derived data and geographic information system. End point rate (EPR) and linear regression rate (LRR) statistical tools in the Digital Shoreline Analysis System (DSAS) were used to estimate historical shoreline change rate between 1973 and 2015. Erosion and accretion of the coastline were delineated from Landsat satellite images for 1973, 1980, 1990, 2000, 2010, and 2015; subsequently, shoreline is predicted for short-term (2025) and long-term (2050) periods. The study showcased that the river mouths of Krishna and Godavari experienced higher rate of change in shoreline position influenced by the deltaic environment and fluvial processes. LRR model prediction depicts the average rate of shoreline change during 2015–2025 will be −4.64 m, while between 2015 and 2050 it will increase to −16.25 m. The study observed that the error between predicted and actual shoreline is higher in the river mouth and deltaic plains. Predicted shoreline position will provide baseline information for adaptation strategies and policy framework for coastal management.

Assessing the shoreline dynamics on Kuakata, coastal area of Bangladesh: a GIS- and RS-based approach

“…The square root of the variance of the residuals is the root mean square error (RMSE), which represents the absolute fit of the model to the data, i.e. how near the observed data points are to the model’s predicted values (Basheer Ahammed & Pandey, 2022). Lower RMSE values imply better fit, whereas larger values suggest error.…”

“…(2019). Basheer and Pandey (2022) studied the antique shoreline variation investigation and its forthcoming forecast by using satellite imagery and geographic information system (GIS). The research area proficient greater rate of amendment in shoreline points predisposed by the deltaic environs and fluvial courses (Basheer & Pandey, 2022).…”

“…Basheer and Pandey (2022) studied the antique shoreline variation investigation and its forthcoming forecast by using satellite imagery and geographic information system (GIS). The research area proficient greater rate of amendment in shoreline points predisposed by the deltaic environs and fluvial courses (Basheer & Pandey, 2022). Some previous study has also been done on coastal zones in the Indian subcontinent as long-term and short-term shoreline undulations (Jana, Maiti, & Biswas, 2016a, b, 2017), seasonal variation on observing and planning of coastal vegetation (Jana et al ., 2016a, b), shoreline vicissitudes with response to sea level (Jana, Biswas, Maiti, & Bhattacharya, 2014), based on the GIS and geospatial methods.…”

The Coastline Paradox: A New Perspective

“…This is widely carried out in practice using satellite and aerial imagery, where Landsat databases, for instance, are used to provide multidecadal analyses of coastline dynamics (Apostolopoulos and Nikolakopoulos, 2021;Bishop-Taylor, 2021;Hu and Wang, 2022). The combination of multitemporal coastline position data with statistical analysis can then be used to make predictions of future changes (Basheer Ahammed and Pandey, 2022;Hossain et al, 2022). In addition, the absolute coastline length may find uses in analyses of the dissipating effects on wave action caused by shoreline roughness and shape.…”

Spatio-Temporal Shorelines Change Model in Totok Bay Southeast Minahasa

“…According to [14,16], "shoreline is defined as the edge of land at the limit of normal height" spring tides; subaerial land margins, often characterized by a boundary towards the sea of terrestrial vegetation. On the cliff beach, it is taken as the foot of the cliff in a high spring tidal level [17]. The shoreline is the water's edge, moving continuously as the tide rises and falls so that there is a low tide, a moderate shoreline, and a tidal shoreline [3].…”