Google Earth: A New Resource for Shoreline Change Estimation—Case Study from Jaffna Peninsula, Sri Lanka

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.

Keywords:

• GIS
• Google earth platform
• DSAS
• remote sensing
• shoreline change

Acknowledgements

We would like to convey our sincere thanks to the Ocean University of Sri Lanka for the facilities provided to prepare GIS maps, to collect remote sensing data including GCPs and for the library facilities. The support given by Mr. S. Suresh who is a government surveyor is highly appreciated for data collection for the beach slope analysis. Mr. Ruchira Jayathilaka who is working as a scientist in National Aquatic Resources Research and Development Agency, Sri Lanka also deserves the thanks as the support given by him in plotting the wave data.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

All authors have contributed in the study by executing remote sensing & GIS data collection, processing, analyzing, statistical applications, map preparations and article writing by covering various aspects of the study.