Generation the coastline change map for Urmia Lake by TM and ETM+ imagery The ratio b2/b5 is greater than one for water and less than one for land in large area of coastal zone. ERMAPPER software uses this ratio as algorithm for separating water from land from TM or ETM+ imagery. This law is exact in coastal zones covered by vegetation, but not in land without vegetative cover. Actually, this law mistakenly signs some of the non-vegetative lands to water. The ratio b2/b4 is greater than one for water and less than one for land in large area of coastal zone. This law is exact in coastal zones covered by soil, but not in land without soil cover. Actually by this law, some of the lands without soil cover are mistakenly signed to water. To solve this problem, we combine two ratios. With this method, we can extract the coastline with higher accuracy. But the problem occurs in some of the coastal zones. Actually, in some areas, the coastline moves toward to water. If the aim is rapid coastline extraction, then it is a supreme method. But when the aim is accurate coastline extraction, then it is not a fine method. To solve this problem, two techniques exist. In the first technique, we utilize a color composite for editing the coastline map. The best color composite for this technique is RGB 543. This color composite nicely depicts water-land interface. Furthermore it is very similar to the true-color composite of earth’s surface. Moreover, it includes the bands that have low correlation coefficient and therefore it contains higher information in comparison to other color composites. The first technique is much time consuming and we need a lot of editing. Therefore we propose the second technique. In the second technique, we utilize histogram thresholding method on band 5 for separating land from water. As we said, any threshold value has been selected; it will be exact in some area, But not in all areas. Therefore we choose threshold value as all water pixels have been classified to water and a lot of land pixels have been classified to land. In this case, few land pixels mistakenly have been classified to water pixels but not vice versa. Now we label water pixels to one and land pixels to zero. Therefore, we achieve a binary image. We name this image “image No. 1”. For obtained image from band ratio technique, also we label water pixels to one and land pixels to zero. We name this image “image No. 2”. Next we multiply two images together. Final obtained binary image represents the coastline accurately. Figure 1 illustrates the steps of second technique.  Figure1. Flowchart of extracting coastlines from images To evaluate the accuracy of this approach, we required to compare the extracted coastline from this approach with the extracted coastline from a ground truth map. Because the lack of a reliable ground truth map we utilized a ground truth image. This ground truth image was provided via fusing the ETM+ multispectral bands with ETM+ panchromatic band. Then we extracted coastline from this ground truth image via visual interpretation. 
Fig. 2 Urmia Lake in Aug-1998 Color composite RGB(543) 
Fig. 3 Urmia Lake in Jun-1989 Color composite RGB(543) 
Fig. 4 Urmia Lake in Aug-2001 Color composite RGB(543) 
Fig. 5 map of shorelines |