Abstract Estimation of shoreline change using satellite images is considered as a very effective method because the coastline is found highly dynamic. This study focuses to develop a methodology to detect shoreline changes using satellite imageries obtained from Google Earth platform. The study was carried out in north-east coastline of Jaffna in Sri Lanka. Shorelines from 2002 to 2017 were delineated on the multi-temporal satellite images in the Google Earth software by visual interpretation and change was detected using Digital Shoreline Analysis System in ArcGIS. Tidal variation, digitizing error, and geometric errors were considered to calculate the uncertainty. Mean End Point Rate, mean Shoreline Change Envelop, mean Net Shoreline Movement, and mean Weighted Linear Regression Rate were used as main shoreline change statistics. Result shows that there is net shoreline accretion of 6.13 ± 8.74 m with an annual rate of deposition of 0.5 m/year. During the study period, 76.12% of the observed shoreline is found accreted while the 23.88% of the shoreline is eroded. Mean Uncertainty of the shoreline is 3.73 ± 0.59 m. The study revealed that the satellite images from Google Earth platform can be used for time series analysis of shorelines after appropriate corrections.

中文翻译：

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Google 地球：海岸线变化估算的新资源——来自斯里兰卡贾夫纳半岛的案例研究

摘要 由于海岸线是高度动态的，因此利用卫星图像估算海岸线变化被认为是一种非常有效的方法。本研究的重点是开发一种使用从 Google 地球平台获得的卫星图像来检测海岸线变化的方法。该研究在斯里兰卡贾夫纳的东北海岸线进行。2002年至2017年的海岸线在谷歌地球软件中的多时相卫星图像上通过目视解译勾画，并使用ArcGIS中的数字海岸线分析系统检测变化。潮汐变化、数字化误差和几何误差被考虑来计算不确定性。平均终点率、平均海岸线变化包络、平均净海岸线移动和平均加权线性回归率被用作主要的海岸线变化统计数据。结果表明，海岸线净增加量为6.13±8.74 m，年沉积量为0.5 m/年。在研究期间，76.12% 的观测海岸线被发现，而 23.88% 的海岸线被侵蚀。海岸线的平均不确定度为 3.73 ± 0.59 m。研究表明，谷歌地球平台的卫星图像经过适当修正后可用于海岸线的时间序列分析。