, “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 of Geography, Environment and Earth Science International,
Environment and Earth Science International, • 2017
Publication Information
Authors
M. E. Basiouny1, S. B. El Kafrawy2, E. A. Ghanem3 and A. S. Taha
Keywords
Remote Sensing, GIS
Journal
Environment and Earth Science International,
Publisher
Not Available
Volume
vol: 10.9734
Issue
10.9734/JGEESI/2017/32086
Pages
32086
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
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.
and 2015 along time period 42 years. These images were used to detect the shoreline
position, 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
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.
and 2015 along time period 42 years. These images were used to detect the shoreline
position, 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
Staff Members - Benha University