Shoreline Change Rate Detеction and Futurе Prediction Using Rеmote Sensing and GIS Tеchniques: A Case Study of Ras EL-Hekma, North Western Coast, Egypt
Journal Title: Journal of Geography, Environment and Earth Science International - Year 2017, Vol 9, Issue 3
Abstract
Shoreline mapping and change rate along the Ras El-Hekma, north west of Egypt has been analyzed. Thresholding band ratio method, in which a thresholding value is selected either by man-machine interaction or by a local adaptive strategy, has been used to extract shorelinе. Digital Shoreline Analysis Systеm (DSAS) used to detect Change ratе of shorelines by EPR (end point rate model). Also future shoreline positions based on precedent shorelines has been predicted and has been corrected. Rates and trends Information of shoreline change can give recommendation to the decision makers to decide the best coastal area to be invested and also can be used to improve understanding of underlying causes and potential effects of coastal erosion/ accretion which can support informed coastal management. Multi-temporal satellite images acquired from (USGS) U.S. Geological Survey in 1973, 1987, 1995,2003 and 2015 along time period 42 years. These images were used to detect the shorelineposition, predict the future shoreline, and to estimate change rate. The results show that the eastern side of study area tends to erosion all the time period. The western area has about 40- 70% erosion and 30-60% accretion depend on date. Overall 42 years the maximum accretion rate is 12 m/year and erosion rate is -9.65m/year. The average rates are defined from -0.8 to -4.25 for erosion and 0.05 to 1.60 for accretion definitely not high. The predicted shoreline was compared with the actual shoreline detected from high resolution satellite imagery of 2015. The positional shift at each sample point is observed. The positional error varies from -49.8 m to 76.3 m. The Rote Mean Square Error (RMSE) for the future predicted shoreline2015 was found to be 15.75 m. also 2020and 2050 shorelines has been predicted and corrected.
Authors and Affiliations
M. E. Basiouny, S. B. El Kafrawy, E. A. Ghanem, A. S. Taha
Keywords
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- EP ID EP321500
- DOI 10.9734/JGEESI/2017/32086
- Views 99
- Downloads 0
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