Detection of shoreline changes using remote sensing and GIS techniques, case study: Coast port city Dayer, Persian Gulf

The coastal areas are always physically and ecologically changing that depends to natural and human factors. Natural factors of coastline changes are evaluated through three

short term changes including the effects of increasing and decreasing of flow; long term changes including climate variation, temporal storms and waves; and random changes including natural unexpected events. These happened changes would effect on coastline changes and coastal areas, and in future would negatively effect on human and human activities and sea communications. Monitoring of coastal areas is an important fact in steady development and environment maintenance. To monitor a coastal area, coastline extraction in various times is an essential task. Coastline is one of the most important linear features on the Earth’s surface showing a dynamic nature. Coastlines are introduced as one of the most important geographical features on the Earth’s surface by International Geographical Data Committee (IGDC), geographically are the intersection of coastal area and the sea water. Accordingly, it is important to produce coastline map and to determine the changes for a secure shipping, resource management, environment maintenance, planning and coastal steady development. Case Study Dair is the one town of Bushehr province in southern Iran and the Persian Gulf coast area. Faults, fractures range of mountains and sea shells on the tracks, show the lowing sea level, the movements of the earth and the organic material being buried with lime flowers at the bottom of the sea.

Remote sensing is one of the best and most reliable methods in monitoring and management of environment and resources. Various methods have been created to extract coastline from satellite images. Since the reflection of water in IR bands are almost Zero and most of vegetation have a bigger reflection versus water, coastline can be extracted from even one band of the image. This extraction can be achieved from Thresholding on one IR band of TM and ETM+ images. Thus, in this study we have used satellite images of TM, ETM and ETM+ Landsat in the years 1987, 2000 and 2006 to monitor the coastline changes of Dair town. Based on results from amplifying methods, contrast enhancement by saturated linear expansion method is more effective in image amplifying, and band 5 is also effective than band 7 in border separation; but since this method only covers the spectral amplifying, in order to extract a distinct border between water and land, it was used along other completing methods, one common of them is temporal amplifying. Thus, various filtering methods were used that edge detection filter on images of band 5 showed better results versus the others. Because the mentioned filter has less effect on existing features in image, extraction of water-land border and even the flat wet lands and water, especially for band 5, was more convenient.

In this paper, using temporal detection of band 5 of Landsat satellite images in 1987, 2000 and 2006, coastline changes of Dair town were extracted. To investigate and determine the spatial changes of coastline, spatial changes from images of 1987, 2000 and 2006 in 50 points with equal distances of 3000 m were measured. Spatial changes of coastline in these points are in such a way that from 1987 to 2000 and 2000 to 2006, the area has encountered a raise in sea level toward the land and a decrease of the area. Minimum and maximum values of spatial change of coastline during 1987 and 2000 are 17 and 2829 m, respectively. Spatial changes of coastline during 2000 and 2006 have been lessened versus the former period, that minimum and maximum values of changes are 2 and 800 m, respectively. Average spatial coastline changes in first and second periods are obtained 502 and 138 m respectively.