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Engineering, Shore Nourishment in Europe 47, 211–235. https://doi.org/10.1016/S03783839(02)00126-6
Su, L., Huang, Y., 2019. Seagrass Resource Assessment Using WorldView-2 Imagery in the
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https://doi.org/10.3390/jmse7040098
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Overview, Environmental Applications of Remote Sensing. IntechOpen.
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Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., Ergul, A., 2009. The Digital Shoreline Analysis
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Thuan, D.H., Almar, R., Marchesiello, P., Viet, N.T., 2019. Video Sensing of Nearshore
Bathymetry Evolution with Error Estimate. Journal of Marine Science and Engineering 7,
233. https://doi.org/10.3390/jmse7070233
Toure, S., Diop, O., Kpalma, K., Maiga, A.S., 2019. Shoreline Detection using Optical Remote
Sensing: A Review. ISPRS International Journal of Geo-Information 8, 75.
https://doi.org/10.3390/ijgi8020075
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Analysis, in: Blaschke, T., Lang, S., Hay, G.J. (Eds.), Object-Based Image Analysis: Spatial
Concepts for Knowledge-Driven Remote Sensing Applications, Lecture Notes in
Shang, X., Chisholm, L.A., 2014. Classification of Australian Native Forest Species Using
Hyperspectral Remote Sensing and Machine-Learning Classification Algorithms. IEEE
Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7, 2481–
2489. https://doi.org/10.1109/JSTARS.2013.2282166
She, X., Qiu, X., Lei, B., 2017. Accurate sea-land segmentation using ratio of average constrained
graph cut for polarimetric synthetic aperture radar data. Journal of Applied Remote Sensing
11, 026023. https://doi.org/10.1117/1.JRS.11.026023
Stafford, D.B., Langfelder, J., 1971. AIR PHOTO SURVEY OF COASTAL EROSION.
Photogrammetric Engineering.
Stive, M.J.F., Aarninkhof, S.G.J., Hamm, L., Hanson, H., Larson, M., Wijnberg, K.M., Nicholls,
R.J., Capobianco, M., 2002. Variability of shore and shoreline evolution. Coastal
Engineering, Shore Nourishment in Europe 47, 211–235. https://doi.org/10.1016/S03783839(02)00126-6
Su, L., Huang, Y., 2019. Seagrass Resource Assessment Using WorldView-2 Imagery in the
Redfish Bay, Texas. Journal of Marine Science and Engineering 7, 98.
https://doi.org/10.3390/jmse7040098
Taibi, N.-E., 2016. Conflict Between Coastal Tourism Development and Sustainability: case of
Mostaganem,
Western
Algeria.
EJSD
5,
13–13.
https://doi.org/10.14207/ejsd.2016.v5n4p13
Teodoro, A.C., 2016. Optical Satellite Remote Sensing of the Coastal Zone Environment — An
Overview, Environmental Applications of Remote Sensing. IntechOpen.
https://doi.org/10.5772/61974
Teodoro, A.C., 2015. Applicability of data mining algorithms in the identification of beach
features/patterns
on
high-resolution
satellite
data.
JARS
9,
095095.
https://doi.org/10.1117/1.JRS.9.095095
Than, V.V., 2015. Modélisation d’érosion côtière : application à la partie Ouest du tombolo de
Giens (These de doctorat). Aix-Marseille.
Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., Ergul, A., 2009. The Digital Shoreline Analysis
System (DSAS) Version 4.0 - An ArcGIS extension for calculating shoreline change
(USGS Numbered Series No. 2008–1278), The Digital Shoreline Analysis System (DSAS)
Version 4.0 - An ArcGIS extension for calculating shoreline change, Open-File Report.
U.S. Geological Survey, Reston, VA. https://doi.org/10.3133/ofr20081278
Thuan, D.H., Almar, R., Marchesiello, P., Viet, N.T., 2019. Video Sensing of Nearshore
Bathymetry Evolution with Error Estimate. Journal of Marine Science and Engineering 7,
233. https://doi.org/10.3390/jmse7070233
Toure, S., Diop, O., Kpalma, K., Maiga, A.S., 2019. Shoreline Detection using Optical Remote
Sensing: A Review. ISPRS International Journal of Geo-Information 8, 75.
https://doi.org/10.3390/ijgi8020075
Tzotsos, A., Argialas, D., 2008. Support Vector Machine Classification for Object-Based Image
Analysis, in: Blaschke, T., Lang, S., Hay, G.J. (Eds.), Object-Based Image Analysis: Spatial
Concepts for Knowledge-Driven Remote Sensing Applications, Lecture Notes in