Remote Sensing Applications and Decision Support

Shifting the waterlines of satellite images to the mean water shorelines considering wave runup, setup, and tidal variation

[+] Author Affiliations
Hsien-Kuo Chang, Wei-Wei Chen, Jin-Cheng Liou

National Chiao Tung University, Department of Civil Engineering, 1001 University Road, Hsinchu, Taiwan, China

J. Appl. Remote Sens. 9(1), 096004 (Sep 25, 2015). doi:10.1117/1.JRS.9.096004
History: Received May 28, 2015; Accepted August 7, 2015
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Abstract.  Shoreline evolution is a simple and common method to illustrate beach erosion or accretion in coastal engineering. Extracted waterlines on different satellite images are sometimes used for shoreline evolution. However, time-varying waterlines for tidal variation and wave runup are different from the shoreline at the mean water level. Waterline evolution may bring about misunderstanding of beach erosion or accretion. In a former study, the one-line shift method was proposed to determine the waterlines on a satellite image and to shift the waterlines to shorelines while only considering the tidal variation. The upward shift extension of the waterline due to wave runup and wave setup is considered. Some acceptable equations of wave runup were examined to correct the waterlines on three satellite images in one month when the foreshore beach slopes were specified. The suggested equation for wave runup includes both wave conditions and an average beachface slope at two points located shoreward and seaward away from mean water level by an equal distance of 62.5 m. When on-site shore bathymetrical measurement is sometimes unavailable, a method of minimizing the difference between the initially guessed and estimated foreshore beach slopes by the one-line shift method is proposed.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Hsien-Kuo Chang ; Wei-Wei Chen and Jin-Cheng Liou
"Shifting the waterlines of satellite images to the mean water shorelines considering wave runup, setup, and tidal variation", J. Appl. Remote Sens. 9(1), 096004 (Sep 25, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096004


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