The Virtual Domain Application Data Center (VDADC): Access to Data in Multiple Formats and Data Visualization

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VAccess A Virtual Remote Sensing Center for
Virginia
Menas Kafatos CEOSR CEOSR URL
http//www.ceosr.gmu.edu
April, 2001
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Earth, Space, Remote Sensing, Data Systems

• CEOSR is involved in several space-related
  interdisciplinary areas
• Space Sciences
• Astrophysics
• Solar Physics
• Earth Observing Earth Sciences
• Data Information Systems (S-I ESIP Project
  Federation)
• Satellite Missions
• Aeronomy of Ice in the Mesosphere (AIM) (Phase
  APolar mesospheric Clouds)
• IMAGE (Imaging the Ionosphere on common platform
  with GIFTS)
• ARGOS (RAD Hard Computing)
• Remote Sensing for Regional Applications
• Hyperspectral
• Virtual RS Center for Virginia

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Current representative graduate student Earth
science, RS data information areas

• Data Management and Knowledge Discovery Approach
  in On-line Earth Science Data Information System
  Design (Ph.D. thesis, summer 1998)
• Hyperspectral Imaging Spectrometer Data Mining
  Using Genetic Algorithms
• Hyperspectral Studies of Virginia Wetlands and
  Coastal Areas
• North American Regional Vegetation Studies from
  1982 to 1992
• Tropical Forest Biomass Density on Barro Colorado
  Island, Panama
• Remote Sensing of Vegetation in South Vietnam and
  Effects of Defoliants
• Lower Tropospheric and Sea Surface Temperature
  Differences as Related to Hurricane Development
  in the Atlantic Ocean
• Interdisciplinary Studies of Climate Changes from
  Interannual to Millenial Phenomena Highlighting
  Cryolithohydroatmospheric Processes and the El
  Nino Southern Oscillation
• Model of Hypothesized Dimethylsulfide-Temperature
  Regulation in Remote Oceans
• Remote Sensing of the Neutral Density Medium in
  the Upper Atmosphere
• Remote Sensing on the MSX Experiment and the
  Ozone Hole
• Image Registration, Parallel Architectures and
  Rain Data
• Remote Sensing of Oil Spills in the Red Sea
• Remote Sensing and floods in Bangladesh

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CEOSR Themes, Projects and Relationships

• Key to Chart
• GCDC Global Change
• Data Center
• DAAC Distributed Active
• Archive Center
• TSDIS TRMM Science
• Data Information System
• SSD Space Sciences Div.
• RSD Remote Sensing Div.
• Research
• Institutional
• Links

NASA GCDC
VIRGINIA
Coop Agreement
SCS
CEOSR
VAcees
DAAC
TSDIS
GMU ISE, AES, GES, Biology ESPP
CHARM
SIESIP
COLA
Regional Projects
DSWA
www.siesip.gmu.edu
Coop Agreement
GSFC Code 600 Space Sciences Directorate
GSFC Code 900 Earth Sciences Directorate
NRL SSD RSD
Earth Science, Data Information
Astrophysics
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RS Leveraging Earth Observing Research Activities

• Leverages existing grants cooperative
  agreements in Earth space science with national
  labs and NASA Headquarters (estimated gt 4M for
  FY2001)
• Has substantial student interest (many from
  industry)
• Couples with State and No. VA focus emphasis in
  Information Technology and Space
• Closely ties to strengths in other related areas
  at COLA and SCS (Climate Dynamics, Atmospheric
  Science) collaborative efforts with other GMU
  units (CAS, ITE)
• Leverages GMU expertise strengths

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INFORMATION TECHNOLOGY STRATEGY

• Development of science scenarios which drive the
  content-based searching to serve particular user
  communities
• Web accessibility
• Content-based browsing
• Integration of tools accessibility with data set
  accessibility to allow meaningful, user-specified
  queries
• Integration of freely/easily accessible
  visualization/ data mining and analysis tools
  with relational data base management system

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VAccessVirtual Remote Sensing Center of
Excellence Providing RS Data Information
Products for Regional Applications in Virginia

• A STATE-WIDE, SATELLITE-DERIVED AND OTHER
  ENVIRONMENTAL DATA, INFORMATION PRODUCTS,
• FOR
• LOCAL, REGIONAL STATE NEEDS WITH
  USER-DETERMINED NEED FOR STUDIES, INFORMATION,
  SOLUTIONS
• AN ALLIANCE BETWEEN 6 UNIVERSITIES LED BY
  CEOSR Initial Funding FY 2001 1M
• Prototyping an operational alliance of academia,
  State interests, NASA the commercial sector

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Vaccess Virtual Remote Sensing Center of
Excellence Providing RS Data Information
Products for Regional Applications in Virginia

• Partners
• GMU
• JMU
• ODU
• Hampton
• Virginia Space Grant Consortium
• UVA
• VT

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State of Virginia and the Use of Remote Sensing
Data
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Virginia Access to Remote Sensing Data - Concept
and ExamplesFigure 1
Special Capability Users
Community Server
Graduate Courses Certificate Courses Distance
Learning Course Materials Instructor
List Schedule Sites
Topography Maps Road Maps Demographic Data
Education Training
Low-Cost Regional Data
Virginias Virtual Remote Sensing
Data Information System
Application DataBases
Wetlands Data Land Classifications Vegetation
Collaboration Support
Algorithms Statistical Tools Protocol
Data Metadata Files
HSI Signature Library
Datasets Satellite Other
Landsat 7 AVHRR MODIS ASTER TRMM SeaWIFS GOES SSM/
I NextRad
Vegetation Structural Materials Roadway
Materials Sources AVIRIS, EOS-1, In Situ
Synthetic Aperture Radar
Statewide Application Licenses
DEM Surface Objects Foliage Penetration Images
Vendor MOUs
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VAccess Support Staff Services
Virginias Virtual Remote Sensing
Data Information System
Staff Services

• Task Virginia-wide Data Access
• Software Licensing Goals
• Minimize cost to obtain/buy
• Data from diverse sources
• Minimize cost to obtain
• state-wide software licenses for
• Academia
• Approach Form small group from
• Industry academia to determine
• Ways to achieve goals
• Benefits User access to more data
• At lower cost
• Providers gain more users along
• with product/tool new ideas

• Outreach
• - Partners and Alliances
• Web page(s) Development
• Brochure Preparation
• Project Management
• Coordination
• Planning
• Integrated Budgeting
• Project Reporting
• Performance Metrics
• PODAR perform other duties as required

Statewide Application Licenses
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• Manage and execute HSI projects and programs for
  the GMU/CEOSR
• Provide research support for other GMU
  departments and other research partners
• Conduct RD in support of these programs
• Manage and execute remote sensing programs for
  CEOSR
• Develop and maintain capability for responding to
  local, state, region, and national emergencies
• Support VA, region, and national hyperspectral
  imagery initiatives

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Hyperspectral Sensing An Enabling Mature
Technology
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Hyperspectral Technology Applications

• Agriculture and Forestry
• vegetation type identification, assessment of
  vegetative stress, crop yield, resource
  monitoring
• Geology
• mapping of minerals and rock types for mineral
  and hydrocarbon exploration
• Environmental
• detection of spills, baseline studies, land use
  planning
• Marine and inland waters
• mapping of shoreline materials, bathymetry, water
  quality
• Civil
• Transportation corridors, city planning

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Figure 1. The Warrenton-Fauquier Airport based
Piper platform is shown with the SAR installed.
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Figure 2. SAR image and topographic retrieval
using WINSAR.
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Reconfiguration of PALDaily data into Tiled
Regions
NOAA/NASA 8-km Pathfinder AVHRR Land (PAL) Data
Set, used in the Production of Vegetation Dynamics
Data Products LAI, fPAR, Land Cover Change...
AVHRR Channel 1 2 and NDVI (Respectively)
Daily Time-series of Egypt 1981-1994
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Customized MODIS Data Applications for V Access
1. Because the MODIS senses all the earths
surface in 36 spectral bands spanning the visible
(0.415 µm) to infrared (14.235µm) spectrum with
at nadir spatial resolution of 1 km, 500 m and
250 m, MODIS remote sensing data are of interest
not only to land and ocean scientists but also to
atmospheric and environmental scientists. 2.
Native MODIS data files are stored in HDF-EOS
(Hierarchical Data Format Earth Observing
System), a file format that does not currently
have wide support. 3. MODIS land product imagery
is in a new map projection called the
Integerized Sinusoidal (ISIN) projection which
is not supported by most existing software
packages. 4. MODIS dataset sizes are too big to
process by users. 5. Customized (subsetted, data
format converted, reprojected and GIS
compatible) MODIS datasets are very important for
most local users. 6. V-Access will provide
customized MODIS Level-1B (MOD02),
Surface reflectance (MOD09), and NDVI/EVI (MOD13)
as starting points.
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Customized MODIS Data Infrastructure for V Access

Near real time MODIS data from GSFC DB
MODIS data on ECS
Subscription
Subsetting software Subsampling
software Reprojection software Mapping
software GIS Conversion software Visualization
software
VAccess MODIS Processing Toolkits
Customized MODIS Datasets in V-Access Database
Web Access by users
ftp
VAccess Users
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Hydrology and Forest Fire

• Objective Provide regional moisture information
  and assessment of fire potential
• Potential Users EOF, DOA, EPA
• Approach develop RS and in situ data set to
  estimate basin scale water budget develop fire
  model
• Output Soil moisture and ET maps from Landsat/MW
  sensors, GOES/MW rainfall, Land Surface
  temperature, vegetation/surface type from AVHRR
  and MW sensors, fire product basin water budget,
  fire potential model
• Validation/ancillary data NOAA surface gauge
  rainfall and temperature, River runoff, DOF
  Historical fire reports

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Natural hazard Monitoring, Prediction and
Assessment

• Objectives Improved regional monitoring,
  assessment and prediction of natural hazards such
  as Hurricane, snowstorm, freezing rain, flash
  flood
• Potential users VDOT, DOA, DOT, EPA, FEMA
• Approach examine RS and in situ data for extreme
  cases to determine model output statistics (MOS)
  bias
• Output Merged GOES/MW rain/snow, model bias,
  soil moisture, flash flood potential, flood area
  assessment, aerosol
• Validation/ancillary data NEXRAD, surface type,
  surface precipitation, wind, temp and upper air
  sounding data, NCEP and regional model model
  output statistics (MOS), weather related traffic
  accident reports, air pollution data, historical
  flood data

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Proposed VIRGINIA ACCESS Center
Architecture2001Figure
Industry User
Student or Educational User
GMU User
Partner User
INet Client Side
Middleware for Search and Browse
Tailored Data Bases By Discipline By Geographic
Area By Community
INet Server Side
Order via INet
Processor(s)
NOAA
GMU
Partners
NASA
Foreign
Satellite Down Link
For Tailored Databases
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GOES Ground Station
AVHRR Ground Station
Filer
Data Storage
Data Storage
Application Servers(Labs)
Production Area(engine)
Partners Data Set
ARCINFO
ENVI
DB Server
Coding Area
Partner Alpha
Partner Beta
Web Host
Users
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Virginia Access to Remote Sensing Data - Roles
of GIS
Topography Maps Road Maps Demographic Data
Distance Learning Support
Low-Cost Regional Data
Course Materials Instructor List Schedule (modules
on integrating GIS/RS analysis)
Virginias Virtual Remote Sensing
Data Information System
These data are mostly in GIS formats. GIS can
provide an integrated environment to bring
together these data and RS data
Collaboration Support
Algorithms Statistical Tools Protocol
Data Metadata Files (spatial analysis and
statistical capabilities in GIS)
Satellite Datasets
Application DataBases
Wetlands Data Land Classifications Vegetation
Landsat 7 AVHRR MODIS ASTER TRMM NextRad (some
RS data are available in GIS formats)
Synthetic Aperture Radar
Statewide Application Licenses (ESRI GIS
sofware Licenses)
DEM Surface Objects Foliage Penetration
Images (DEM and topo data are handled
efficient by raster-based GIS)
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• Data Analysis and Visualization Tools
• ENVI/IDL
• GIS (ArcView/Arc/Info)
• Splus
• Training on Tools
• Local usage
• Regional applications/Scientific research
• Integrate tools with data for access through the
  Internet
• General system setup
• Setup for specific research work
• Knowledge Discovery Data Mining
• Content-based search
• Knowledge discovery from RS data and other Earth
  science data
• Web-based Tools
• Data access, leverage existing tools
•         VDADC
•         SIESIP/GDS
•         DIAL

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Use of Metadata ServerExample Interface with
GrADS/DODS Server
User/Scientist
General User
Call out
MetadataBrowse/Search
GrADSClient
DODS URL
Client workstation
GrADS/ DODSServer
Metadata(XML)Server
Remote systems
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The Future Distributed Client-Server Architecture
Clients
Metadata request/result (XML)
Data request/ result (DODS)
DIMES Distributed Metadata Server
DIMES Register
DIMES
DIMES
Ingest Tool Box
Ingest Tool Box
...
...
To be developed
Server (DODS, GrADS/DODS)
Server (DODS, GrADS/DODS)
DATA
DATA
Super Data Server
Super Data Server