results as represented in the previous pages refer just to
the most famous values among the others in the papers
being studied and do not propose the best of them
because every index has its advantages and drawbacks
and moreover the final choice is depended on many
factors. We believe that the results represent the researcher’s favorable trend of the materials and methods about
the same issue: the coastal erosion and the shoreline
evolution.
Disclosure statement
The authors declare no conflict of interest.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit
sectors.
ORCID
Dionysios Apostolopoulos
http://orcid.org/0000-00030956-7049
Konstantinos Nikolakopoulos
http://orcid.org/00000003-1028-9541
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Number of
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2014
Management of Coastal Erosion Using Remote Sensing and GIS Techniques
471
Paul M. Cooley, David G.
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471
Mujabar, P.S. et.al.,2013
Shoreline change analysis along the coast between Kanyakumari and Tuticorin of India using remote
sensing and GIS
457
Raju Aedla, 2015
Automatic Shoreline Detection and Change Detection Analysis of Netravati-GurpurRivermouth Using
Histogram Equalization and Adaptive Thresholding Techniques
159
Cabezas-Rabadán, Carlos
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Characterizing beach changes using high-frequency Sentinel-2 derived shorelines on the Valencian coast
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151
M.A. Davidson et al., 2010 Forecasting seasonal to multi-year shoreline change
150
Bera, Rakesh & Maiti,
Ramkrishna, 2019
Quantitative analysis of erosion and accretion (1975–2017) using DSAS-A study on Indian Sundarbans
146
Bu-Li Cui, Xiao-Yan Li,
2011
Coastline change of the Yellow River estuary and its response to the sediment and runoff (1976–2005)
143
Salim, Fatima et al., 2018 Application of a Geomatics Approach for the Diachronic Study of the Meditterannean Coastline Case of
Tangier Bay
134
Robertson, William et.
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Mapping Shoreline Position Using Airborne Laser Altimetry
129
EUROPEAN JOURNAL OF REMOTE SENSING
259
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