The current study investigates the shoreline forecasting results combining the IRS and SPOT medium resolution satellite imagery with the high-resolution air-photos. The littoral area of the bay of Katakolo situated in the Prefecture of Ilia’s, Greece, has been used as a test site. Past shoreline positions have been demarcated, through on-screen digitizing method, for the years of 1945, 1960, 1965, 1968, 1975, 1987, and 1996, based on the respective high-resolution images. The shoreline evolution for the 1945-1996 period was estimated for each dataset via the Linear Regression Rate (LRR) using for the 1996 the shorelines derived from the High Resolution (HR), SPOT, and IRS datasets respectively. The results were cross-validated using the R-squared, the Root Mean Square Error (RMSE), and the Mean Annual Error (MAE) coefficient methods. In addition, future position of the shoreline (forecasted shoreline) was estimated for 10 years (2006) by alternating the reference shoreline of the 1996 with the relative shoreline derived from the IRS and SPOT-3 satellite images respectively. The integrated forecasting function of the fifth version of the Digital Shoreline Analysis System (DSAS) tool of the ArcGIS software was used for the computations. The End Point Rate (EPR) was calculated for the 1996 - 2006 period, using the 1996 actual and the 2006 forecasted shorelines based on the SPOT and the IRS data, and compared to the respective rates derived from the high-resolution actual shorelines. Moreover, the Shoreline Change Envelope (SCE) rates were computed in order to estimate the mean rate of distance between the 2006 actual and forecasted shoreline of each dataset. The images have been orthorectified and georeferenced to Hellenic Geodetic Reference System of 1987 (Greek Grid) using Leica Photogrammetry Suite (LPS), while transects every 30 meters along the coastline were created and used for the measurements. It was proved that although both datasets provide similar results, the SPOT (Pan) images seem to have an advantage, while the comparison based on the forecasting models should be avoided in sites where infrastructures have taken place as they distort the results. |
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