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.

Coastal areas are attractive for human populations as they are important areas of business and socio-economic activities. The Prefecture of Western Greece is experiencing population movement from the urban to the coastal areas causing nuisance and changes to the marine environment. These changes need to be assessed systematically in order to build models that can predict the evolution in the future. In addition, except for the man-made infrastructures, natural phenomena such as undulation, wind and coastal currents affect the shape of the beach, the shoreline and the seabed.

Remote sensing is an efficient way to measure these changes repeatedly using high resolution satellite data, air photos and airborne Lidar in conjunction with Digital Surface Models (DSMs) and orthophoto maps. These methods have disadvantages as they are high cost, especially in cases where multitemporal data is deeded.

Unmanned aerial vehicles (UAV) photogrammetry, offers a reliable alternative solution to the acquisition of high accuracy spatial data along the littoral zone, representing a rapid low-cost tool for coastline monitoring.