4.5 Article

Shoreline change rate estimation and its forecast: remote sensing, geographical information system and statistics-based approach

Journal

Publisher

SPRINGER
DOI: 10.1007/s13762-013-0196-1

Keywords

Coastal management; Correlation coefficient; Human intervention; Linear regression; Littoral cell; Root-mean-square error

Funding

  1. Ministry of Earth Sciences, New Delhi, India through MMDP [MoES/11-MRDF/1/35/P/08-PC-III]

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The present study indicates that coastal geomorphology is controlled by the natural processes and anthropogenic activities. The changes in shoreline positions of Udupi coast, western India, are investigated for a period of 98 years using multi-dated satellite images and topographic maps. The study area has been divided into four littoral cells and each cell into a number of transects at uniform intervals. Further, past shoreline positions have been demarcated and future positions are estimated for 12 and 22 years. The shoreline change rate has been estimated using statistical methods-end point rate, average of rates and linear regression-and cross-validated with correlation coefficient and root-mean-square error (RMSE) methods. Resultant changes from natural processes and human interventions have been inferred from the estimated values of the back-calculated errors. About 53 % of transects exhibit +/- 10 m RMSE values, indicating better agreement between the estimated and satellite-based shoreline positions, and the transects closer to the cell boundaries exhibit similar to 57 % uncertainties in shoreline change rate estimations. Based on the values of correlation coefficient and RMSE, the influence of natural processes and human interventions on shoreline changes have been calculated. The cells/transects dominated by natural processes record low RMSE values, whereas those influenced by human interventions show lower correlation coefficient and higher RMSE values. The present study manifests that the results of this study can be very useful in quantifying shoreline changes and in prediction of shoreline positions.

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