Abstract

For 43 years, multi-dated satellite imagery is used to examine shifts in shorelines and potential location on shorelines for Dr. Abdul Kalam Island, in the Bay of Bengal, India. A Normalized Difference Water Index with object-based classification system and automatic shoreline extraction tool is used to retrieve the shoreline automatically. To calculate the rates of shoreline change and future positions, based on empirical observations, the simple statistical model, such as EPR and LR models are used. The erosion/accretion scenario is also analyzed for the 1976, 1989, 1997, 2008 and 2018 shoreline of Landsat imaging.Results showsnorth of Dr. Abdul Kalam Island is subjected to high deposition rates and the south part having high erosion rates in the vicinity of the Dhamara Estuary and Maipura River. The short-term (2023) and long-term (2028) shoreline positions are predicted on the basis of the delineated shoreline. Around 63% of transect’s RMSE values varies between ±10 m, showing better agreement among the estimated shoreline positions and satellite-based ones. The results of the study can be very useful for the quantification of shoreline changes, shoreline forecasting and precautionary measures for anti-satellite missile launching centre.

摘要

43 年来，多日期卫星图像被用于检查印度孟加拉湾阿卜杜勒卡拉姆博士岛海岸线的变化和海岸线上的潜在位置。具有基于对象的分类系统和自动海岸线提取工具的归一化差异水指数用于自动检索海岸线。为了计算海岸线变化率和未来位置，根据经验观察，使用简单的统计模型，例如 EPR 和 LR 模型。还分析了 1976 年、1989 年、1997 年、2008 年和 2018 年 Landsat 成像海岸线的侵蚀/增生情景。结果显示，阿卜杜勒卡拉姆岛以北的沉积率较高，而南部附近的侵蚀率较高。达马拉河口和迈普拉河。短期（2023 年）和长期（2028 年）海岸线位置是根据划定的海岸线预测的。大约 63% 的样带 RMSE 值在 ±10 m 之间变化，表明估计的海岸线位置和基于卫星的位置之间的一致性更好。研究结果对岸线变化的量化、岸线预测和反卫星导弹发射中心的预防措施非常有用。