A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach
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...
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doaj-56482a231a5d4dd599c9662b3eed32b62020-11-24T23:17:08ZengMDPI AGRemote Sensing2072-42922016-07-018757310.3390/rs8070573rs8070573A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based ApproachLauren Dunkin0Molly Reif1Safra Altman2Todd Swannack3Army Engineer Research and Development Center, 3903 Halls Ferry Road, Vicksburg, MS 39180, USAArmy Research and Development Center, Joint Airborne Lidar Bathymetry Technical Center of Expertise, 7225 Stennis Airport Road, Suite 100, Kiln, MS 39556, USAArmy Engineer Research and Development Center, 3903 Halls Ferry Road, Vicksburg, MS 39180, USAArmy Engineer Research and Development Center, 3903 Halls Ferry Road, Vicksburg, MS 39180, USANesting 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.http://www.mdpi.com/2072-4292/8/7/573LIDARsea turtlemorphologynesting habitatremote sensing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lauren Dunkin Molly Reif Safra Altman Todd Swannack |
spellingShingle |
Lauren Dunkin Molly Reif Safra Altman Todd Swannack A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach Remote Sensing LIDAR sea turtle morphology nesting habitat remote sensing |
author_facet |
Lauren Dunkin Molly Reif Safra Altman Todd Swannack |
author_sort |
Lauren Dunkin |
title |
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach |
title_short |
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach |
title_full |
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach |
title_fullStr |
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach |
title_full_unstemmed |
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach |
title_sort |
spatially explicit, multi-criteria decision support model for loggerhead sea turtle nesting habitat suitability: a remote sensing-based approach |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2016-07-01 |
description |
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. |
topic |
LIDAR sea turtle morphology nesting habitat remote sensing |
url |
http://www.mdpi.com/2072-4292/8/7/573 |
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