Abstract
Abstract. Coastal management requires rapid, up-to-date, and correct information. Thus, coastal movements have primary importance for coastal managers. For monitoring the change of shorelines, remote sensing data are some of the most important information and are utilized for differentiating any detections of change on shorelines. It is possible to monitor coastal changes by extracting the coastline from satellite images. In the literature most of the algorithms developed for optical images have been discussed in detail. In this study, an algorithm which extracts coastlines efficiently and automatically by processing SAR (Synthetic Aperture Radar) satellite images has been developed. A data set of ALOS Palsar image of Fine Beam Double (FBD) HH-HV polarized data has been used. PALSAR image has L-band data, and has a 14 MHz bandwidth and 34.3 degrees look angle. Data were acquired in ascending geometry. Ground resolution of PALSAR image was resampled to 15 m to amplitude image. Zonguldak city, lies on the northwest costs of Turkey, has been selected as the test area. An algorithm was developed for automatic coastline extraction from SAR images. The algorithm is encoded in a C__ environment. To verify the results the algorithm was applied on two PALSAR images gathered in two different date as 2007 and 2010. The results of automatic coastline extraction obtained from SAR images were compared to the results derived from manual digitizing. Random control points which are seen on each image were used. The average differences of selected points were calculated.
Highlights
As a peninsula country Turkey has a coastline more over than 8300 km, and 1700 km of this is surrounded by Black Sea
For the study area coastline detection is important because this region has mining which are located at the coast and has international ports
To verify the results two dated 2007 and 2010 Phased Array type L-band Synthetic Aperture Radar (PALSAR) images are acquired and the algorithm was applied on four images in total
Summary
As a peninsula country Turkey has a coastline more over than 8300 km, and 1700 km of this is surrounded by Black Sea. Due to fact that it is needed to update coastline information and morphological changes versus any natural disaster. Since this area suffer from flooding and erosion problems. ISODATA classification method is used to observe long term shoreline changes (Yu, et al, 2011). Two enhanced Level Set Algorithm (LSA) which is based on active contours or snakes are applied on Radarsat imagery by Ouyang et al (2010). Another wavelet based edge detection algorithm is developed for coastal change detection from ERS data by Chen et al. The algorithm was successfully applied on optical data such as CORINA, IRS-1D and Landsat in previous study (Bayram et al, 2008)
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