VAccess: A Virtual Remote Sensing
Center for Virginia
Menas Kafatos
CEOSR
CEOSR URL: http://www.ceosr.gmu.edu
CEOSR
April, 2001
CSI
GMU
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 A:Polar
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
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
CEOSR
•Remote Sensing on the MSX Experiment and the Ozone Hole
• Image Registration, Parallel Architectures and Rain Data
CSI
•Remote Sensing of Oil Spills in the Red Sea
•Remote Sensing and floods in Bangladesh
GMU
CEOSR Themes, Projects and
Key to Chart
Relationships
NASA
GCDC
DAAC
VIRGINIA
Coop
Agreement
SCS
CEOSR
TSDIS
VAcees
•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
GMU
CHARM
SIESIP
Regional
Projects
COLA
www.siesip.gmu.edu
Coop
Agreement
GSFC
Code 600
Space Sciences
Directorate
DSWA
NRL
Astrophysics
SSD
RSD
ISE, AES,
GES, Biology
ESPP
GSFC
Earth Science, Data
Information
Code 900
Earth Sciences
Directorate
RS: Leveraging Earth Observing Research
Activities
•Leverages existing grants & cooperative agreements in
Earth & space science with national labs and NASA
Headquarters (estimated > $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, IT&E)
•Leverages GMU expertise & strengths
CSI
CEOSR
GMU
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

CEOSR
CSI
GMU
VAccess:Virtual 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 USERDETERMINED 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
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
State of Virginia and the Use
of Remote Sensing Data
E n v ir o n m e n t a l I s s u e s
N a tu ra l H a z a rd s
F lo o d s :
- F la s h & S u r g e
S to rm s
H u r r ic a n e s
A b n o r m a l T id e s
W ild fir e s
D ro u g h ts
U V
L ig h t n in g
M a n -M a d e E v e n ts
- P la n n e d
- A c c id e n t a l
- N e fa r io u s
P o llu t io n
- A g r ic u lt u r e
C h e m ic a ls
- W a s te P ro d u c ts
S p ills
- O il
- C h e m ic a ls
- T o x ic s
Fum es
- A u to E x h a u s t
L a n d R e s o u rc e
M is m a n a g e m e n t
- E x c e s s iv e R u n o ff
- W a t e r w a y C lo g s
- S ilt
U rb a n G ro w th &
C o n s t r u c t io n
R e g io n s
C o a s ts
R iv e r C o u r s e s
C it ie s
F a r m in g A r e a s
In te re s ts
& V ie w p o in t s
P re p a re d n e s s
A ssessm ent
M it ig a t io n
P r o v id e r s
- O r b it a l S c ie n c e s
A g r ic u lt u r a l I n t e r e s t s
L an d C over
F o re s try
W a t e r U t iliz a t io n
L a n d P la n n in g
H ig h w a y P la n n in g
Virginia Access to Remote Sensing Data
- Concept and Examples
Figure 1
Special Capability
Users
Graduate Courses
Certificate Courses
Distance Learning
Course Materials
Instructor List
Schedule
Sites
Algorithms
Statistical
Tools
Protocol Data
Metadata Files
Education
&
Training
Collaboration
Support
Landsat 7
AVHRR
MODIS
ASTER
TRMM
SeaWIFS
GOES
SSM/I
NextRad
Community
Server
Low-Cost
Regional
Data
Virginia’s
Virtual Remote
Sensing Data
Information
System
Datasets:
Satellite
& Other
Vendor
MOUs
Application
Data
Bases
HSI
Signature
Library
Statewide
Application
Licenses
Synthetic
Aperture
Radar
Topography Maps
Road Maps
Demographic Data
DEM
Surface Objects
Foliage Penetration
Images
Wetlands Data
Land
Classifications
Vegetation
Vegetation
Structural Materials
Roadway Materials
Sources – AVIRIS,
EOS-1, In Situ
Virginia’s
Virtual Remote
Sensing Data
Information
System
VAccess Support Staff Services
Task: Virginia-wide Data Access
& Software Licensing Goals
-Minimize cost to obtain/buy
Statewide Data from diverse sources
Application -Minimize cost to obtain
Licenses 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
Staff Services
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
Hyperspectral Imagery Laboratory
Director
Spectral Research Division
Team Leader
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Instrumentation Division
Team Leader
Applications Division
Team Leader
Manage and execute HSI projects and programs for the GMU/CEOSR
Provide research support for other GMU departments and other research
partners
Conduct R&D 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
Hyperspectral Sensing
An Enabling Mature Technology
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
Figure 1. The Warrenton-Fauquier Airport based Piper platform is shown with the SAR installed.
Figure 2. SAR image and topographic retrieval using WINSAR.
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
Customized MODIS Data Applications for V Access
1. Because the MODIS senses all the earth’s 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.
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
Web Access
by users
Customized MODIS
Datasets in
V-Access Database
VAccess
MODIS
Processing
Toolkits
ftp
VAccess
Users
Hydrology and Forest Fire
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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
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
Proposed VIRGINIA ACCESS Center Architecture
2001
Figure
GMU
User
Industry
User
Student or
Educational
User
Partner
User
INet
Client Side
Middleware for Search and Browse
Tailored Data Bases
By Discipline
By Geographic Area
By Community
Order via
INet
Processor(s)
Foreign
GMU
INet
Server Side
Partners
Satellite
Down Link
For Tailored Databases
NASA
NOAA
GOES
Ground
Station
Data
Storage
Application
Servers(Labs)
ARCINFO
ENVI
Filer
Production
Area(engine)
DB
Server
AVHRR
Ground
Station
Data
Storage
Coding
Area
Web Host
Users
Partner’s
Data Set
Partner
Alpha
Partner
Beta
Virginia Access to Remote Sensing Data
- Roles of GIS
Course Materials
Instructor List
Schedule
(modules on integrating
GIS/RS analysis)
Distance
Learning
Support
Algorithms
Statistical
Collaboration
Tools
Support
Protocol Data
Metadata Files
(spatial analysis
and statistical
capabilities
Landsat 7
in GIS)
Satellite
AVHRR
MODIS
Datasets
ASTER
TRMM
NextRad
(some RS
data are
available
in GIS formats)
Low-Cost
Regional
Data
Virginia’s
Virtual Remote
Sensing Data
Information
System
Topography Maps
Road Maps
Demographic Data
These data are mostly in GIS
formats. GIS can provide an
integrated environment to
bring together these data and
RS data
Application
Data
Bases
Statewide
Application
Licenses
(ESRI GIS
sofware
Licenses)
Synthetic
Aperture
Radar
DEM
Surface Objects
Foliage Penetration
Images
(DEM and topo data
are handled efficient
by raster-based GIS)
Wetlands Data
Land
Classifications
Vegetation
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
1.
General system setup
2.
Setup for specific research work
•
Knowledge Discovery & Data Mining
1.
2.
•
Content-based search
Knowledge discovery from RS data and other Earth science data
Web-based Tools
1.
2.
3.
4.
5.
6.
7.
8.
Data access, leverage existing tools
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VDADC
SIESIP/GDS
DIAL
WMT prototype (International standard)
Metadata access
Metadata ingesting/creating
DBMS
XML technology (DIMES)
Use of Metadata Server
Example: Interface with
GrADS/DODS Server
User/Scientist
General User
Call out
GrADS
Client
Metadata
Browse/
Search
DODS URL
Client workstation
GrADS/
DODS
Server
Metadata
(XML)
Server
Remote systems
The Future: Distributed ClientServer Architecture
Clients
DIMES: Distributed
Metadata Server
DIMES Register
Ingest DIMES
Tool Box
To be
developed
Server (DODS,...
Metadata
request/result
(XML)
Ingest DIMES
Tool Box
...
Server (DODS,
GrADS/DODS)
DATA
Super Data Server
Data request/
result (DODS)
GrADS/DODS)
DATA
Super Data Server