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Remote Sens. 2016, 8(7), 573; doi:10.3390/rs8070573

A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach

1
Army Engineer Research and Development Center, 3903 Halls Ferry Road, Vicksburg, MS 39180, USA
2
Army Research and Development Center, Joint Airborne Lidar Bathymetry Technical Center of Expertise, 7225 Stennis Airport Road, Suite 100, Kiln, MS 39556, USA
*
Author to whom correspondence should be addressed.
Received: 12 April 2016 / Accepted: 30 June 2016 / Published: 6 July 2016
(This article belongs to the Special Issue Remote Sensing in Coastal Environments)
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Abstract

Nesting habitat for the federally endangered loggerhead sea turtle (Caretta caretta) were designated as critical in 2014 for beaches along the Atlantic Coast and Gulf of Mexico. Nesting suitability is routinely determined based on site specific information. Given the expansive geographic location of the designated critical C. caretta nesting habitat and the highly dynamic coastal environment, understanding nesting suitability on a regional scale is essential for monitoring the changing status of the coast as a result of hydrodynamic forces and maintenance efforts. The increasing spatial resolution and temporal frequency of remote sensing data offers the opportunity to study this dynamic environment on a regional scale. Remote sensing data were used as input into the spatially-explicit, multi-criteria decision support model to determine nesting habitat suitability. Results from the study indicate that the morphological parameters used as input into the model are well suited to provide a regional level approach with the results from the optimized model having sensitivity and detection prevalence values greater than 80% and the detection rate being greater than 70%. The approach can be implemented in various geographic locations to better communicate priorities and evaluate management strategies as a result of changes to the dynamic coastal environment. View Full-Text
Keywords: LIDAR; sea turtle; morphology; nesting habitat; remote sensing LIDAR; sea turtle; morphology; nesting habitat; remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Dunkin, L.; Reif, M.; Altman, S.; Swannack, T. A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach. Remote Sens. 2016, 8, 573.

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