Abstract
Decrease of habitat, coastal erosion, and shoreline changes are recent issues for coastal management. In this study, an algorithm which extracts coastlines efficiently and automatically by processing low- or medium-resolution satellite images has been developed. The junction of sea and land is a common result yielded by the automatic coastline extraction method. In this study, CORONA (1963), IRS-1D (2000), and LANDSAT-7 (2001) satellite images for the same region in Istanbul, Turkey were used. A novel algorithm was developed for automatic coastline extraction. The algorithm is encoded in a C++ environment. The results of automatic coastline extraction obtained from different images were compared to the results derived from manual digitizing. Random control points which are seen on every image were used. The average differences of selected points were calculated. Obtained results from selected points were rendered as 3 pixels on the CORONA and IRS-1D images and as 2 pixels on the LANDSAT-7 image. These show that the differences are similar, although different images were used. On the other hand, the results are acceptable compared to manual digitizing.
Original language | English |
---|---|
Pages (from-to) | 983-991 |
Number of pages | 9 |
Journal | Journal of Coastal Research |
Volume | 24 |
Issue number | 4 |
DOIs | |
Publication status | Published - Jul 2008 |
Keywords
- Coastline extraction
- Image processing
- Remote sensing
- Segmentation