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Remote Sens. 2013, 5(11), 5662-5679; doi:10.3390/rs5115662

Assessing the Performance of a Northern Gulf of Mexico Tidal Model Using Satellite Imagery

1
Department of Civil, Environmental and Construction Engineering, University of Central Florida, 12800 Pegasus Blvd., Suite 211, Orlando, FL 32816, USA
2
NOAA-CREST, City College/City University of New York, New York, NY 10031, USA
3
Coast Survey Development Laboratory, Office of Coast Survey, National Ocean Service, National Oceanic and Atmospheric Administration, 1315 East West Highway, N/CS13, Silver Spring, MD 20910, USA
4
Department of Biology, University of Central Florida, 4110 Libra Drive., Orlando, FL 32816, USA
5
University Corporation for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307, USA
*
Author to whom correspondence should be addressed.
Received: 15 September 2013 / Revised: 29 September 2013 / Accepted: 28 October 2013 / Published: 1 November 2013
(This article belongs to the Special Issue Hydrological Remote Sensing)
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Abstract

Tidal harmonic analysis simulations along with simulations spanning four specific historical time periods in 2003 and 2004 were conducted to test the performance of a northern Gulf of Mexico tidal model. A recently developed method for detecting inundated areas based on integrated remotely sensed data (i.e., Radarsat-1, aerial imagery, LiDAR, Landsat 7 ETM+) was applied to assess the performance of the tidal model. The analysis demonstrates the applicability of the method and its agreement with traditional performance assessment techniques such as harmonic resynthesis and water level time series analysis. Based on the flooded/non-flooded coastal areas estimated by the integrated remotely sensed data, the model is able to adequately reproduce the extent of inundation within four sample areas from the coast along the Florida panhandle, correctly identifying areas as wet or dry over 85% of the time. Comparisons of the tidal model inundation to synoptic (point-in-time) inundation areas generated from the remotely sensed data generally agree with the results of the traditional performance assessment techniques. Moreover, this approach is able to illustrate the spatial distribution of model inundation accuracy allowing for targeted refinement of model parameters. View Full-Text
Keywords: model validation; tides; ADCIRC; multi-sensor; remote sensing; SAR; inundation detection model validation; tides; ADCIRC; multi-sensor; remote sensing; SAR; inundation detection
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Medeiros, S.C.; Hagen, S.C.; Chaouch, N.; Feyen, J.; Temimi, M.; Weishampel, J.F.; Funakoshi, Y.; Khanbilvardi, R. Assessing the Performance of a Northern Gulf of Mexico Tidal Model Using Satellite Imagery. Remote Sens. 2013, 5, 5662-5679.

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