摘要：Rosetta Promontory, Egypt has been suffering from a continuous erosion problem. The dramatic retreatment was observed during the last century. It is basically due to the construction of Aswan High Dam in 1964, which reduced the flow and sediment discharges. In this paper, four Landsat images (two Thematic Mapper and two Enhanced Thematic Mapper) covering the period from 1984 to 2014 were used. These Landsat images were radio-metrically and geometrically corrected, and then, multi-temporal post-classification analysis was performed to detect land cover changes, extracting shoreline positions to estimate shoreline change rates of the Nile delta coast around Rosetta Promontory. This method provides a viable means for examining long-term shoreline changes. Four categories, including seawater, developed (agriculture and urban), sabkhas (salt-flat), and undeveloped areas, were selected to evaluate their temporal changes by comparing the four selected images. Supervised classification technique was used with support vector machine algorithm to detect temporal changes. The overall accuracy assessment of this method ranged from 97% to 100%. In addition, the shoreline was extracted by applying two different techniques. The first method is based on a histogram threshold of Band 5, and the other uses the combination of histogram threshold of Band 5 and two band ratios (Band 2/Band 4 and Band 2/Band 5). For land cover change detection from 1984 to 2014, it was found that the developed area that increased by 9% although the land in the study area has been contracted by 1.6% due to coastal erosion. The shoreline retreat rate has decreased more than 70% from 1984 to 2014. Nevertheless, it still suffers from significant erosion with a maximum rate of 37 m/year. In comparison to ground survey and different remote sensing techniques, the established trend of shoreline change extracted using histogram threshold was found to be closely consistent with these studies rather than combining band ratio with histogram threshold.
关键词：remote sensing; change detection; land cover; shoreline; Rosetta
