Research

The long distance movement of marine turtles is one of the wonders of the natural world, with recapture techniques showing how some species move thousands of kilometers across the ocean (Meylan, 1995). The Mid-Atlantic serves as a host environment for a number of sea turtle species that encompasses their seasonal migration routes. Currently, out of the six turtles species all are labeled as either threatened or endangered under the Endangered Species Act.
Previous research suggests that migration routes are strongly influenced by two factors: sea surface temperature and chlorophyll concentrations. Studies in the past that investigate sea turtles and their correlation with Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) and chlorophyll concentration have only focused on one turtle species, the Caretta caretta (loggerhead turtle).

This study included two species of sea turtles, the Caretta caretta and Chelonia mydas (green turtle). These turtles were tracked along the Mid-Atlantic to determine if a correlation exists between migration routes, sea surface temperature, chlorophyll concentrations, and wind data. Archived AVHRR sea surface temperature and OrbView-2 SeaWiFS chlorophyll data were derived, processed, and analyzed at the Center of Excellence in Remote Sensing Education and Research (CERSER) located on the campus of Elizabeth City State University. CERSER has a TeraScan 1.5m System that is configured to ingest data from polar orbiting satellites. The system contains a suite of software which was utilized for the processing and analysis of the data. In addition, AVHRR sea surface temperature and QuikSCAT wind data were utilized from the Jet Proportions Laboratory.

Before processing the data, TeraCapCon, a software package used for scheduling and viewing images that are ingested into the TeraScan System, was used to locate data. Once data was located it was retrieved from archival tape using the TeraScan pass disk. After retrieval AVHRR data was processed using the command ‘hrptin’. The command ‘outliers’ was then used to correct for noisy data. Once the noisy data was corrected it was calculated for the sea surface temperature using the command ‘nitpix’. ‘Nitpix’ converts brightness temperature to sea surface temperature in areas that are determined to be cloud free. ‘Nitpix’ is an implementation of the Multichannel sea surface temperature (MCSST) algorithm. The AVHRR data was then ready for analysis.
Before the SeaWifs data could be processed it first had to be decrypted. CERSER has a two week delayed license. With this license SeaWifs data must remain on the system for two weeks before it can be processed. After decryption of the data it was processed using the command ‘seawifsin’ and calculated for chlorophyll concentrations using the command ‘swcolor’. ‘Swcolor’ implements the official SeaWiFS ocean color algorithms to derive chlorophyll, pigment concentrations, and aerosol optimal depth. The SeaWiFS data was then ready for processing.

This project was a continuation of the paper “A Determination of Temporal and Spatial Distribution, Migratory Patterns, and Habitats for Sea Turtles using AVHRR”.