How Sun Microsystems Opengl and Java Three-Dimensional Can Enhance the CERSER Remote Sensing Education and Research Two-Dimensional Satellite Imagery Program

The ONR Network team is using Sun’s three-dimensional (3D) technologies such as OpenGL and Java 3D for Solaris to visualize Satellite Imagery data sets on an UNIX based SGI Irex or Solaris Scalable Processor Architecture (SPARC) platform. OpenGL and Java 3D for Solaris uses the high performance graphics card installed in the Sun Sunblade 100 which are located in room 115 of Lester Hall. Sun OpenGL API (Application Programming Interface) for Solaris software is a 3D graphics application programming interface (API) based on the OpenGL industry-standard specification for developing interactive 3D graphics applications on the Solaris platform. It provides graphics software developers a complete set of graphics functions for defining, rendering, and animating 3D models. It incorporates a broad set of powerful visualization and imaging extensions such as 3D texture mapping support, multitexturing, and imaging operations.

To deliver integrate Sun’s 3D imagery performance; the ONR team will utilize the NVIDIA graphics and digital media processor technology that SUN has bundled with Sun Sunblade 100 (Sun Java Workstations W1100z and W2100z). The combined technology of NVIDIA and SUN allows Sun OpenGL implementation for Solaris that is based on the AMD Opteron(TM) processor with Direct Connect Architecture to provide a higher bus bandwidth, increased memory bandwidth, and higher rendering speeds will allow the CERSER Remote Sensing Education and Research two dimensional Satellite Imagery program to process large data sets in 3D.

NOAA’s Educational Partnership Program Internship
NOAA Center for Coastal Fisheries and Habitat Research (CCFHR) at Beaufort, North Carolina

Determining the Maximum Depth of Seagrass Beds along the Southern Outer Banks with an Optical Model
Mentors: Dr. Jon Hare, Dr. Jud. Kenworthy, Dr. Patrick Biber

The goals of this project are to develop a long-term record of seagrass bed extent, focusing primarily on the historical changes that have occurred to the deep-edge, and tie this in with historical changes in water-quality. The data gathered from this internship project will be used to calibrate a model of light attenuation for seagrass habitat requirements. This model is being developed as a tool to assist managers with monitoring water-quality to protect seagrasses, a critical estuarine habitat in North Carolina.

ArcMap was used to create maps that show how Chlorophyll a, TSS, and CDOM affect water quality. Pathfinder Office was used to locate the deep-edge sites, and to put the site locations into ArcMap. Each map showed how one component’s value affected water quality for one day. These raster layers were then combined using the spatial analyst extention in ArcMap to form a raster layer that gave important information on how predefined thresholds were being exceeded. The thresholds are the highest values of CDOM, TSS, and Chlorophyll that can be present and still allow enough sunlight to get to the seagrass. Areas where the thresholds were exceeded are unfavorable for seagrass growth.

Future developments for this model aim to include remote-sensing information in near-real time to enable timely and appropriate management actions to be made.

2003-2004 ONR Remote Sensing

A Determination of Temporal and Spatial Distribution, Migratory Patterns, and Habitats for Sea Turtles using AVHRR
Mentor: Keisha Harrison Wilkins

Of the six sea turtle species that are found in U.S. waters or that nest on U.S. beaches, all are designated as either threatened or endangered under the Endangered Species Act (U.S. Fish and Wildlife Service, 1998). These sea turtles were listed because, to different degrees, their populations had declined largely as a result of human activities (Committee of Sea Turtle Conservation, 1990). Recent population studies have concluded that the number of females that nest in the Southeast United States is continuing to decline. Successful conservation of large marine vertebrates requires an adequate understanding of their temporal and spatial distribution, migratory patterns, and habitat utilization (Godley, 2003).

Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature data was utilized from the Center of Excellence in Remote Sensing Education and Research (CERSER) on the campus of Elizabeth City State University. CERSER currently has a 1.5 TeraScan System which is able to ingest AVHRR and SeaWiFs data. This data was combined with turtle point source data to determine if there was a correlation between the sea surface temperature and the location of sea turtles. AVHRR sea surface temperature datasets were also collected and analyzed from NOAA’s CoastWatch program. The CoastWatch data was then compared with data from CERSER for validation. Turtle point source data was overlaid onto sea surface temperature data to provide a means of visualization. Maps will also be developed to track and display the migratory patterns of sea turtles.

Destruction of feeding and nesting habitats and pollution of the world’s oceans are all taking a serious toll on the remaining sea turtle populations. By identifying the distribution, migratory patterns, and habitats of sea turtles preventive measures can be taken to ensure that this endangered species is protected from human destruction. This will also enable the development of strategies for protecting sea turtles.