GIS-based visualization and map server efforts in support of marine fisheries and ecosystem management Tiffany C. Vance (AFSC) and Christopher Moore (PMEL) Nazila Merati PMEL Jason Fabritz OMAO Hal Mofjeld PMEL

u VRML based visualizations for the Cordell Bank NMS u Using ArcIMS map servers for intra-layer calculations u Java/Java3D and ArcGIS Engine as a framework for a “scientific GIS”

Introduction u Visualizations of spatially complicated datasets are used to enable scientists to understand complex physical and biological processes. u These geo-visualizations are also becoming a way to disseminate the data as a coherent package. u Rather than distributing discrete datasets, a project can disseminate a view of the data the recipient has the ability to move through the data can add and remove layers can query to datasets at specific three-dimensional locations.

u VRML based visualizations for the Cordell Bank NMS u Using ArcIMS map servers for intra-layer calculations u Java/Java3D and ArcGIS Engine as a framework for a “scientific GIS”

Project goals u To create interactive visualizations of GIS data for the Sanctuary u To enable viewers to see the Sanctuary as a volume, not a flat map u To test distribution of the visualizations u To test integration of GIS displays and true 3D visualizations

Cordell Bank Cordell Bank Marine Sanctuary is a 526- square mile sanctuary located 50 miles northwest of San Francisco. The Sanctuary encompasses Cordell Bank - a pinnacle rising from the seafloor to within 120 feet of the sea surface - and the surrounding waters.

Datasets for the Sanctuary Bathymetry Physical characteristics- CTD Hydroacoustic survery Bottom type data SST images Coastlines and boundaries

Visualization of the Sanctuary

Standard tools and plug-ins within browsers (VRML players, animation players such as RealPlayer, javascript tools) to enable users to manipulate the visualizations. Viewing a visualization

VRML generation - fencelines Isosurfaces, plumes and vertical fenceline plots created using EVS- Pro. EVS-Pro allows for 3-D kriging and fenceline plots Fenceline of towed instrument data

VRML generation - isosurfaces 3D temperature plumes and isosurfaces created in EVS-Pro are exported and combined with the VRML 2.0 output from ArcScene (8 degree temperature isosurface and CTD cast positions)

Viewing visualizations u User loads the visualization into a VRML-aware web browser u Coastline, bathymetry and topography data in the VRML window. u 3-D navigation control in the VRML window u Can load, view and animate data as the scene is rotated and scaled. u Radio-button choices are given for dataset choices u Animation controls appear as time dependent data are loaded.

u VRML based visualizations for the Cordell Bank NMS u Using ArcIMS map servers for intra-layer calculations u Java/Java3D and ArcGIS Engine as a framework for a “scientific GIS”

Project goals u To create a series of tools to allow user defined intra and inter-layer calculations and comparisons within the framework of ArcIMS u To allow PMEL to be able to calculate the population at risk from tsunamis u To allow NMML and AFSC to calculate biophysical measures

Background u Internet map servers (IMS) are used to disseminate information allow users to perform queries to extract information to serve data u All line offices in NOAA are using IMS applications to serve data u A drawback of off-the-shelf map servers is that one cannot do on-the-fly calculations on layers, or between layers

WebMapCalculator architecture ArcIMS/ JSP Application HTTP Post Website Server Side calculator File Access Shape Files Java Servlet Application Calculated Results Using ArcIMS on Solaris with JAVA JDK 1.4, Running Image Server, Feature Server and Extract Server Path to Files Include Shapefiles in ArcIMS Map Workspace

Demonstration project - tsunami modeling in Puget Sound u PMEL’s Tsunami Inundation Mapping Effort (TIME) u Products for use by emergency managers u Involves ingesting data from municipalities NOAA model output observational data u Data products are maps - static and live data reports produced using GIS analysis

TIME data u Data are disseminated as ArcView projects. Layers include inundation fields census products run up model results animations. u Distributed to emergency managers via CD

WebMapCalculator for TIME Input: u Gridded wave height data from a tsunami model u Population of Seattle area by day and night u Elevation data Output: u A polygon that shows resulting at-risk population

Output from the IMS u Inundation IMS shows users inundation results from model maximum velocities day/night populations natural hazards shoreline data u Data sources have metadata associated with the layers

Toolkits to be added u RACEBASE dataset of trawl survey data - intra-layer calculations between fisheries datasets and physical oceanography datasets such as water temperature or salinity u NMML - ability to query tracked mammal results to determine swimming speeds, distanced traveled

u VRML based visualizations for the Cordell Bank NMS u Using ArcIMS map servers for intra-layer calculations u Java/Java3D and ArcGIS Engine as a framework for a “scientific GIS”

Project Goals u To extend the capabilities of ArcGIS to form the foundation of a “scientific GIS” for fisheries oceanography u To integrate existing oceanographic analytical tools with ArcGIS u To take advantage of visualization tools such as VRML and Java3D to provide truly three-dimensional visualizations

Programming options u ArcObjects/VB - limited to single platform, limitations of VB u ArcGIS Engine - platform independent, cost? u Open source GIS tools such as GRASS, MapServer, PostGIS, GeoTools and VisAD - documentation/support

System Diagram

Algorithms u UNESCO routines for water properties u Oceanographic Analyst (ArcView 3.2) u Matlab tools - SEA-MAT package u USGS sedx package ions/sedxinfo.html u VTK toolkit - for volume analysis

Test Case - Mixed layer depth The depth to which water is well mixed. This has ramifications for fish and planktonic organisms, also for nutrients. Surface layer sits above the thermocline. Defined as the layer where the temperature is within 0.5° of the average surface temperature or where the potential density is within of the surface average

Conductivity-temperature-depth (CTD) data

Java test case u MLD algorithm from VB to Java u GeoTools toolkit shapefile reader (Java) used to read shapefile u Created a new application in Java to calculate the MLD and output a VTK OpenGL window u VTK wrapped in Java u Can also display MLD shapefile created in ArcGIS version

3-D Visualization at PMEL 1. Perspective: 2. Relative Motion: 3. Stereo: Why 3-D?

1. Perspective High frequency spikes in the bathymetry data are obvious in the 3D plot (right) and are obscured in the 2D plot above. Calculations of bathymetry gradients to identify regions of internal tide generation would be impacted by these spikes in the bathymetry data. Bathymetry in Astoria Canyon offshore from the Columbia River outflow in Washington State, in 2D and 3D.

2. Relative Motion (Interaction) The ability to judge an object’s distance through the use of relative motion

3. Stereographic Virtual Reality Fish larvae in a canyon Stereo gives the scientist true depth perception Stereo Mono Ocean currents

21 ImmersaDesk A Next Generation Internet (NGI) Testbed The ImmersaDesk: 4’ x 5’ rear projecting screen near immersive 1024 x 768 x 96 Hz driven by SGI Onyx2 Two R12000 Processors 250 MHz Infinite Reality Graphics

GeoWall PC-driven projection system Stereo Commodity graphics cards Inexpensive NOAA-Tech

Host computer polarizing filter Projector (R frame) Projector (L frame) polarizing filter Polarization- preserving screen Supports *any* stereo-equipped software: vis5d, visAD, stereo VRML viewers, etc. The GeoWall Approach

Problem: We’re pushing the computational limits with our models. Even high-end graphics cards aren’t up to the challenge Let’s look at a real-world example…

PMEL scientist models Gulf of Alaska Uses NCSA supercomputer cluster to model Large domain (540 x 320 x 32) = 5.5 million points Generating files on the order of a terabyte (1000 gigs) Our models aren’t just run on a linux cluster, they are run on several clusters, connected using Grid technology:

TeraGrid - connecting heterogeneous clusters Myrinet Chicago & LA DTF Core Switch/Routers Sun Server Federation 7.8 TF Power4 1 TF Itanium2 Fibre Channel 2 TF Itanium2 9.2 TF Madison 0.5 TF Itanium2 90 TB 1.5 TF Itanium2/Madison 20 TB Datawulf IA-32 SDSC NCSA CaltechArgonne Quadrics PSC 6TF Alpha EV TF Alpha EV7 300 TB 160 TB

VisAD – Java-based Graphics Tool VisAD uses Java3D to render 3-D scenes Java provides a Remote Method Invocation (RMI) that allows data to be rendered at each “node” of a cluster, and then stitched together at the client. host (also a node) client (PC) Cluster nodes RMI internet *VisAD and RMI framework for parallel rendering by Bill Hibbard:

VisAD test program

Viz Clusters: Distributed Rendering with the GeoWall2 Developed at EVL & SDSC, SCRIPPS 15 LCD screens in 3x5 array driven by small Linux cluster Total resolution: 8000x3600 Video compositing allows each node to render from distributed file - up to 38 Terabytes of data on the screen! Software: JuxtaView, ParaView Scalable: Personal GW is 2x2

Future activities u Framework for 3D modeling of environmental factors u Use of Java to handle temporal analyses u Other graphics outputs u Integration with ArcIMS site

This work was funded by NOAA’s HPCC program ( and the Sanctuaries Program ( ). For more information about the Pacific Marine Environmental Laboratory's visualization efforts, please visit the PMEL visualization page at and

Questions?