Automatic Shoreline Extraction from High-resolution Ikonos Satellite Imagery

Shoreline mapping and shoreline change detection are critical for safe navigation, coastal resource management, coastal environmental protection, and sustainable coastal development and planning. This paper reports the results of IKONOS geopositioning accuracy improvement, showing that a 1-2 meter accuracy can be achieved from 1mresolution IKONOS Geo stereo images. The experiment indicated that a simple adjustment model, e.g., either the Affine or the Scale &Offset model, is effective both to eliminate the systematic errors found in the vendor-provided Rational Function (RF) coefficients and to significantly improve the accuracy of 3D geopositioning. Aiming to automate shoreline mapping, we investigated a novel approach for automatic extraction of shorelines from highresolution IKONOS imagery. In the first step of the proposed approach, the image is segmented into homogeneous regions by mean shift segmentation. Then, the major water body is identified and an initial shoreline is generated. The final shoreline is obtained by local refinement within the boundaries of the candidate regions adjacent to the initial shoreline. We test the approach using 4mand 1m-resolution IKONOS images in a pilot project area along the Lake Erie shore. Test results show that the proposed approach is capable of extracting shorelines from IKONOS images with little human interaction. A method for 3D-shoreline generation is also discussed. The accuracies of the extracted shorelines from 4m XS and 1m Pan stereo images are estimated to be 8.5m and 2-3m respectively.