Automatic Coastline Detection Using Image Enhancement and Segmentation Algorithms
Erdem Emin Maraş1, Mustafa Caniberk2, Hadi Hakan Maraş3
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1Department of Geomatics, Ondokuz Mayıs University, Samsun, Turkey
2Department of Photogrammetry, General Command of Mapping, Ankara, Turkey
3Department of Computer Engineering, Cankaya University, Ankara, Turkey
Submission date: 2016-02-29
Final revision date: 2016-07-11
Acceptance date: 2016-07-11
Publication date: 2016-11-24
Pol. J. Environ. Stud. 2016;25(6):2519–2525
Coastlines have hosted numerous civilizations since the earliest times of mankind due to the advantages they offer such as natural resources, transportation, arable areas, seafood, trade, and biodiversity. Coastal regions should be monitored vigilantly by planners and control mechanisms, and any changes in these regions should be detected with its human or natural origin, and future plans and possible interventions should be formed in these aspects to maintain ecological balance, sustainable development, and planned urbanization.
Integrated coastal zone management (ICZM) provides an important tool to reach that goal. One of the important elements of ICZM is the detection of coastlines. While there are several methods to detect coastlines, remote sensing methods provide the fastest and the most efficient solutions.
In this study, color infrared, grayscale, RGB, and fake infrared images were processed with the median filtering and segmentation software developed within the study, and coastal lines were detected by the edge detection method. The results show that segmentation with fake infrared images derived from RGB images give the best results.