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Correction: Kim, H.; et al. Geospatial Assessment of the Post-Earthquake Hazard of the 2017 Pohang Earthquake Considering Seismic Site Effects. ISPRS Int. J. Geo-Inf. 2018, 7, 375
Open AccessReview

Shoreline Detection using Optical Remote Sensing: A Review

Laboratoire d’Electronique Informatique Télécommunication et Energies Renouvelables, Université Gaston Berger, 32000 Saint-Louis, Sénégal
INSA Rennes, CNRS, IETR (Institut d’Electronique et de Télécommunication de Rennes), Univ Rennes, UMR 6164, F-35000 Rennes, France
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(2), 75;
Received: 30 October 2018 / Revised: 20 December 2018 / Accepted: 20 January 2019 / Published: 5 February 2019
(This article belongs to the Special Issue Natural Hazards and Geospatial Information)
With coastal erosion and the increased interest in beach monitoring, there is a greater need for evaluation of the shoreline detection methods. Some studies have been conducted to produce state of the art reviews on shoreline definition and detection. It should be noted that with the development of remote sensing, shoreline detection is mainly achieved by image processing. Thus, it is important to evaluate the different image processing approaches used for shoreline detection. This paper presents a state of the art review on image processing methods used for shoreline detection in remote sensing. It starts with a review of different key concepts that can be used for shoreline detection. Then, the applied fundamental image processing methods are shown before a comparative analysis of these methods. A significant outcome of this study will provide practical insights into shoreline detection. View Full-Text
Keywords: beach monitoring; coastline; feature extraction; shoreline beach monitoring; coastline; feature extraction; shoreline
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Toure, S.; Diop, O.; Kpalma, K.; Maiga, A.S. Shoreline Detection using Optical Remote Sensing: A Review. ISPRS Int. J. Geo-Inf. 2019, 8, 75.

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