Luca, C., Leonardo, D., Sousa, L., Michael, P., & Alves, F.
(2013). Geomatics for integrated coastal zone management: Multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region.
Journal of Coastal Research. 65(sp2), 1349–1354. https://
doi.org/10.2112/SI65-228.1
Luca, C., Leonardo, D., Μgpina, P., Eduardo, O., Fátima, A.,
& Michael, P. (2017). Integrating remote sensing and GIS
techniques for monitoring and modeling shoreline evolution to support coastal risk management. GIScience &
Remote Sensing, 5(3),1–21. https://doi.org/10.1080/
15481603.2017.1376370
Maglione, P., Parente, C., & Vallario, A. (2015). High resolution
satellite images to reconstruct recent evolution of domitian
coastline. American Journal of Applied Sciences, 12(7), 506–
515. https://doi.org/10.3844/ajassp.2015.506.515
Malarvizhi, K., Kumar, S., & Porchelvan, P. (2016). Use of
high resolution Google earth satellite imagery in land use
map preparation for urban related applications. Procedia
Technology, 24, 1835–1842. https://doi.org/10.1016/j.
protcy.2016.05.231
Manjulavani, K., Supriya, V. M., Suhrullekha, M., & Harish,
B. (2017) Detection of shoreline change using geo-spatial
techniques along the coast between Kanyakumari and
Tuticorin 2017 IEEE International Conference on Power,
Control, Signals and Instrumentation Engineering
(ICPCSI), Chennai, 2822–2825. https://doi.org/10.1109/
ICPCSI.2017.8392235
Marghany, M., & Hashim, M. (2010a). Developing adaptive
algorithm for automatic detection of geological linear features using RADARSAT-1 SAR data. International Journal
of Physical Sciences, 5(14), 2223–2229. https://www.research
gate.net/publication/235781068_Developing_adaptive_algo
rithm_for_automatic_detection_of_geological_linear_fea
tures_using_RADARSAT-1_SAR_data
McFeeters, S. K. (1996). The use of normalized difference
water index (NDWI) in the delineation of open water
features. International Journal of Remote Sensing, 17(7),
1425–1432. https://doi.org/10.1080/01431169608948714
Mitra, S., Mitra, D., & Abhisek, S. (2017). Performance testing
of selected automated coastline detection techniques applied
on multispectral satellite imageries. Earth Sci. Inform, 10(3),
321–330. https://doi.org/10.1007/s12145-017-0289-3
Mohammad, M., Gholamreza, A., & Mohammad, S. (2018).
Integration of spectral histogram and level set for coastline detection in SAR images. IEEE Transactions on
Aerospace and Electronic Systems, 55(2), 810–819.
https://doi.org/10.1109/TAES.2018.2865120
Mohammed, E., Elham, M. W., & Hassan, F. (2019).
Assessment and prediction of shoreline change using
multi-temporal satellite images and statistics: Case study
of Damietta coast, Egypt. Applied Ocean Research, 82,
274–282.apor.2018.11.009https://doi.org/10.1016/j
Mörner, N., & Klein, P. (2017). Coastal Erosion in Yasawa
Islands, Fiji. Natural Science, 9(5), 136–142. https://doi.
org/10.4236/ns.2017.95014
Mujabar, P. S., & Chandrasekar, N. (2013). Shoreline change
analysis along the coast between Kanyakumari and Tuticorin
of India using remote sensing and GIS. Arab J Geosci, 6(3),
647–664. https://doi.org/10.1007/s12517-011-0394-4
Murray, F. (2013). Shoreline changes interpreted from
multi-temporal aerial photographs and high resolution
satellite images: Wotje Atoll, Marshall Islands. Remote
Sensing of Environment, 135, 130–140. https://doi.org/
10.1016/j.rse.2013.03.027
Nageswara Rao, K., Subraelu, P., Venkateswara Rao, T., Hema
Malini, B., Ratheesh, R., Bhattacharya, S., & Rajawat, A. S.
(2008). (2008) Sea-level rise and coastal vulnerability: An
assessment of Andhra Pradesh coast, India through remote
sensing and GIS. J Coast Conserv Coast Conserv, 12(4), 195–
207. https://doi.org/10.1007/s11852-009-0042-2
Nan, X. (2018). Detecting coastline change with all available
Landsat data over 1986–2015: A case study for the State of
Texas, USA. Atmosphere, 9(3), 107. https://doi.org/10.
3390/atmos9030107
Nico, V., Alessandra, S., Gianluca, M. M., & Damiani, L.
(2017). New algorithms for shoreline monitoring from
coastal video systems. Earth Science Informatics. https://
doi.org/10.1007/s12145-017-0302-x
Niedermeier, A., Hoja, D., & Lehner, S. (2005). Topography
and morphodynamics in the German Bight using SAR
and optical remote sensing data. Ocean Dynamics, 55(2),
100–109. https://doi.org/10.1007/s10236-005-0114-2
Nikolakopoulos, K., Kyriou, A., Koukouvelas, I., Zygouri,
V., & Apostolopoulos, D. (2019). Combination of aerial,
satellite, and UAV photogrammetry for mapping the
diachronic coastline evolution: The case of Lefkada
Island. ISPRS Int. J. Geo Inf, 8(11), 489. https://doi.org/
10.3390/ijgi8110489
Nikolakopoulos Konstantinos, G., & George, D. (2017)
Estimating the accuracy of vectors derived from open data,
Proc. SPIE 10428, Earth Resources and Environmental
Remote Sensing/GIS Applications VIII, 104280N. Warsaw,
Poland. https://doi.org/10.1117/12.2278275
Nikolakopoulos Konstantinos, G., Kozarski, D., & Kogkas, S.
(2017) Coastal areas mapping using UAV photogrammetry,
Proc. SPIE 10428, Earth Resources and Environmental
Remote Sensing/GIS Applications VIII, 104280O. Wasaw,
Poland. https://doi.org/10.1117/12.2278121
Nino, C., Renato, H., Mikheil, E., Giorgi, K., Zurab, J., Nana,
B., & George, L. (2015). Close range photogrammetry in
the survey of the coastal area geoecological conditions (on
the example of portugal), Earth Sciences. special issue:
Modern Problems of Geography and Anthropology, 4 (5–
1), 35–40. 2015. https://doi.org/10.11648/j.earth.s.
2015040501.17
Nordstrom, K. F. (2004). Beaches and Dunes of Developed
Coasts. Cambridge University Press. https://doi.org/10.
1017/CBO9780511549519
Pajak, M. J., & Leatherman, S. (2002). The high water line as
shoreline indicator. Journal of Coastal Research, 18(2), 329–
337. https://www.researchgate.net/publication/279560697_
The_high_water_line_as_shoreline_indicator
Pantanahiran, W. (2019). Using remote sensing data for
calculating the coastal erosion in Southern Τthailand.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci,
XLII-3/W7, 51–56. https://doi.org/10.5194/isprsarchives-XLII-3-W7-51-2019
Papakonstantinou, A., Topouzelis, K., & Pavlogeorgatos, G.
(2016). Coastline zones identification and 3D coastal
mapping using UAV spatial data. ISPRS Int. J. GeoInformation, 5(6), 75. https://doi.org/10.3390/ijgi5060075
Paravolidakis, V., Moirogiorgou, K., Ragia, L., Zervakis, M.,
& Synolakis, C. (2016). Coastline extraction from aerial
images based on edge detection. ISPRS Ann.
Photogramm. Remote Sens. Spat. Inf. Sci, 3(8), 153–158.
https://doi.org/10.5194/isprs-annals-III-8-153-2016
Pardo-Pascual, E. J., Jaime, A.-C., Luis, R. A., & Jesús, P.-V.
(2012). Automatic extraction of shorelines from Landsat
TM and ETM+ multi-temporal images with subpixel
precision. Remote Sensing of Environment, 123, 1–11.
https://doi.org/10.1016/j.rse.2012.02.024
Paul, E., Horn, D., Dornbusch, U., Thomas, I., & Dan, A.
(2015) Monitoring mixed sand and gravel beaches using
EUROPEAN JOURNAL OF REMOTE SENSING
263
(2013). Geomatics for integrated coastal zone management: Multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region.
Journal of Coastal Research. 65(sp2), 1349–1354. https://
doi.org/10.2112/SI65-228.1
Luca, C., Leonardo, D., Μgpina, P., Eduardo, O., Fátima, A.,
& Michael, P. (2017). Integrating remote sensing and GIS
techniques for monitoring and modeling shoreline evolution to support coastal risk management. GIScience &
Remote Sensing, 5(3),1–21. https://doi.org/10.1080/
15481603.2017.1376370
Maglione, P., Parente, C., & Vallario, A. (2015). High resolution
satellite images to reconstruct recent evolution of domitian
coastline. American Journal of Applied Sciences, 12(7), 506–
515. https://doi.org/10.3844/ajassp.2015.506.515
Malarvizhi, K., Kumar, S., & Porchelvan, P. (2016). Use of
high resolution Google earth satellite imagery in land use
map preparation for urban related applications. Procedia
Technology, 24, 1835–1842. https://doi.org/10.1016/j.
protcy.2016.05.231
Manjulavani, K., Supriya, V. M., Suhrullekha, M., & Harish,
B. (2017) Detection of shoreline change using geo-spatial
techniques along the coast between Kanyakumari and
Tuticorin 2017 IEEE International Conference on Power,
Control, Signals and Instrumentation Engineering
(ICPCSI), Chennai, 2822–2825. https://doi.org/10.1109/
ICPCSI.2017.8392235
Marghany, M., & Hashim, M. (2010a). Developing adaptive
algorithm for automatic detection of geological linear features using RADARSAT-1 SAR data. International Journal
of Physical Sciences, 5(14), 2223–2229. https://www.research
gate.net/publication/235781068_Developing_adaptive_algo
rithm_for_automatic_detection_of_geological_linear_fea
tures_using_RADARSAT-1_SAR_data
McFeeters, S. K. (1996). The use of normalized difference
water index (NDWI) in the delineation of open water
features. International Journal of Remote Sensing, 17(7),
1425–1432. https://doi.org/10.1080/01431169608948714
Mitra, S., Mitra, D., & Abhisek, S. (2017). Performance testing
of selected automated coastline detection techniques applied
on multispectral satellite imageries. Earth Sci. Inform, 10(3),
321–330. https://doi.org/10.1007/s12145-017-0289-3
Mohammad, M., Gholamreza, A., & Mohammad, S. (2018).
Integration of spectral histogram and level set for coastline detection in SAR images. IEEE Transactions on
Aerospace and Electronic Systems, 55(2), 810–819.
https://doi.org/10.1109/TAES.2018.2865120
Mohammed, E., Elham, M. W., & Hassan, F. (2019).
Assessment and prediction of shoreline change using
multi-temporal satellite images and statistics: Case study
of Damietta coast, Egypt. Applied Ocean Research, 82,
274–282.apor.2018.11.009https://doi.org/10.1016/j
Mörner, N., & Klein, P. (2017). Coastal Erosion in Yasawa
Islands, Fiji. Natural Science, 9(5), 136–142. https://doi.
org/10.4236/ns.2017.95014
Mujabar, P. S., & Chandrasekar, N. (2013). Shoreline change
analysis along the coast between Kanyakumari and Tuticorin
of India using remote sensing and GIS. Arab J Geosci, 6(3),
647–664. https://doi.org/10.1007/s12517-011-0394-4
Murray, F. (2013). Shoreline changes interpreted from
multi-temporal aerial photographs and high resolution
satellite images: Wotje Atoll, Marshall Islands. Remote
Sensing of Environment, 135, 130–140. https://doi.org/
10.1016/j.rse.2013.03.027
Nageswara Rao, K., Subraelu, P., Venkateswara Rao, T., Hema
Malini, B., Ratheesh, R., Bhattacharya, S., & Rajawat, A. S.
(2008). (2008) Sea-level rise and coastal vulnerability: An
assessment of Andhra Pradesh coast, India through remote
sensing and GIS. J Coast Conserv Coast Conserv, 12(4), 195–
207. https://doi.org/10.1007/s11852-009-0042-2
Nan, X. (2018). Detecting coastline change with all available
Landsat data over 1986–2015: A case study for the State of
Texas, USA. Atmosphere, 9(3), 107. https://doi.org/10.
3390/atmos9030107
Nico, V., Alessandra, S., Gianluca, M. M., & Damiani, L.
(2017). New algorithms for shoreline monitoring from
coastal video systems. Earth Science Informatics. https://
doi.org/10.1007/s12145-017-0302-x
Niedermeier, A., Hoja, D., & Lehner, S. (2005). Topography
and morphodynamics in the German Bight using SAR
and optical remote sensing data. Ocean Dynamics, 55(2),
100–109. https://doi.org/10.1007/s10236-005-0114-2
Nikolakopoulos, K., Kyriou, A., Koukouvelas, I., Zygouri,
V., & Apostolopoulos, D. (2019). Combination of aerial,
satellite, and UAV photogrammetry for mapping the
diachronic coastline evolution: The case of Lefkada
Island. ISPRS Int. J. Geo Inf, 8(11), 489. https://doi.org/
10.3390/ijgi8110489
Nikolakopoulos Konstantinos, G., & George, D. (2017)
Estimating the accuracy of vectors derived from open data,
Proc. SPIE 10428, Earth Resources and Environmental
Remote Sensing/GIS Applications VIII, 104280N. Warsaw,
Poland. https://doi.org/10.1117/12.2278275
Nikolakopoulos Konstantinos, G., Kozarski, D., & Kogkas, S.
(2017) Coastal areas mapping using UAV photogrammetry,
Proc. SPIE 10428, Earth Resources and Environmental
Remote Sensing/GIS Applications VIII, 104280O. Wasaw,
Poland. https://doi.org/10.1117/12.2278121
Nino, C., Renato, H., Mikheil, E., Giorgi, K., Zurab, J., Nana,
B., & George, L. (2015). Close range photogrammetry in
the survey of the coastal area geoecological conditions (on
the example of portugal), Earth Sciences. special issue:
Modern Problems of Geography and Anthropology, 4 (5–
1), 35–40. 2015. https://doi.org/10.11648/j.earth.s.
2015040501.17
Nordstrom, K. F. (2004). Beaches and Dunes of Developed
Coasts. Cambridge University Press. https://doi.org/10.
1017/CBO9780511549519
Pajak, M. J., & Leatherman, S. (2002). The high water line as
shoreline indicator. Journal of Coastal Research, 18(2), 329–
337. https://www.researchgate.net/publication/279560697_
The_high_water_line_as_shoreline_indicator
Pantanahiran, W. (2019). Using remote sensing data for
calculating the coastal erosion in Southern Τthailand.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci,
XLII-3/W7, 51–56. https://doi.org/10.5194/isprsarchives-XLII-3-W7-51-2019
Papakonstantinou, A., Topouzelis, K., & Pavlogeorgatos, G.
(2016). Coastline zones identification and 3D coastal
mapping using UAV spatial data. ISPRS Int. J. GeoInformation, 5(6), 75. https://doi.org/10.3390/ijgi5060075
Paravolidakis, V., Moirogiorgou, K., Ragia, L., Zervakis, M.,
& Synolakis, C. (2016). Coastline extraction from aerial
images based on edge detection. ISPRS Ann.
Photogramm. Remote Sens. Spat. Inf. Sci, 3(8), 153–158.
https://doi.org/10.5194/isprs-annals-III-8-153-2016
Pardo-Pascual, E. J., Jaime, A.-C., Luis, R. A., & Jesús, P.-V.
(2012). Automatic extraction of shorelines from Landsat
TM and ETM+ multi-temporal images with subpixel
precision. Remote Sensing of Environment, 123, 1–11.
https://doi.org/10.1016/j.rse.2012.02.024
Paul, E., Horn, D., Dornbusch, U., Thomas, I., & Dan, A.
(2015) Monitoring mixed sand and gravel beaches using
EUROPEAN JOURNAL OF REMOTE SENSING
263