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VAccess Team Meeting

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Title: VAccess Team Meeting


1
VAccess Team Meeting
First Meeting of VAccess Team 19th Floor 301
East Byrd Street Virginia Economic Development
Partnership Richmond, Virginia July 9, 2001

GMU ODU JMU VT UVA WM VSGC Hampton
2
VAccess A Virtual Remote Sensing Information
Access Center for Regional Applications in the
Commonwealth of Virginia
Menas Kafatos CEOSR
GMU ODU JMU VT UVA WM VSGC Hampton
CEOSR URL http//www.ceosr.gmu.edu VAccess
URL http//www.VAccess.gmu.edu
July, 2001
3
VA julyVAccess Discussions - July 9, 200110th 1
100PM Introduction to VAccess
Menas
Kafatos Introductions, Overview, Status of
VAccess 115PM Global EO Data for Regional
Applications James McManus 125PM H S I
Technology, Algorithms and Applications Richard
Gomez 135PM Environmental Scenarios George
Taylor 145PM Infrastructure, GIS Other
Tools Ruixin Yang 155PM VAccess
Process Hank Wolf 205PM Landscape
Epedemiology Tom Allen 225PM Visualization
Testbed James Barnes 245PM Advan
ced Analysis Techniques for RS Data Pat
McCormick 305PM Break
GMU ODU JMU VT UVA WM VSGC Hampton
4
VAccess Discussions - July 9, 2001
320PM Virginia Space Grant Consortium Mary
Sandy 345PM Interactive Internet GIS/RS
Tutorial James Perry 405PM Natural Resources
Applications Randy Wynne 425PM IR Atmospheric
Sensor Gaby Laufer 445PM Summary Action
Items, TAC Meeting Plans, Schedule Menas
Kafatos 500PM End of Meeting 530PM Optional
Dinner Discussions of Any Open Issues

GMU ODU JMU VT UVA WM VSGC Hampton
5
Earth, Space, Remote Sensing, Data Systems in
CEOSR
  • 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 VAccess

GMU ODU JMU VT UVA WM VSGC Hampton
6
VAccessVirtual Remote Sensing Information Access
Center 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

GMU ODU JMU VT UVA WM VSGC Hampton
7
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
  • VIMS (William Mary)
  • VT

GMU ODU JMU VT UVA WM VSGC Hampton
8
State of Virginia and the Use of Remote Sensing
Data
GMU ODU JMU VT UVA WM VSGC Hampton
9
Proposed Initial VAccess Data Sets for
Prototyping Applications
  • Vegetation Products (agriculture forestry)
  • AVHRR data from NDVI, LAI, ect.
  • MODIS 250m, 500m, 1000m
  • Pollution runoff-related products (Chesapeake
    Bay, ect.)
  • EO-1 (HSI) AVIRIS (HSI) Landsat
  • LU/LC Products
  • EO-1(HSI) AVIRIS (HSI) Landsat
  • Merged Products
  • SAR HSI
  • HSI visible (on Orion sounding rocket-
    possibly for the future)
  • Ocean Products
  • (possibly) SST data from AVHRR
  • Sea WiFS (selected products)
  • Littoral regions (NEMO HSI future?)
  • Natural Hazards (hurricanes, fires, ect.)
  • TRMM
  • GOES
  • High Resolution, Commercial, Remote Sensing Data
  • TBD (in consultation with the Advisory
    Committee and the NASA Data Buy program)

10
The Utility of AVHRR and MODIS Time-series Data
in Remote Sensing Application Studies
James McManus GMU July 9, 2001
11
Introduction
The purpose of the talk is to explain how VAccess
can utilize data from the
  • NOAAs Advanced Very High Resolution Radiometer
    (AVHRR) and
  • NASAs Moderate Resolution Imaging Spectrometer
    (MODIS)

In remote sensing application studies I will
also explain the strengths of this type of data,
in land surface applications, relative to higher
resolution satellite data.
12
Polar-Orbiting Operational Environmental
Satellites (POES)
AVHRR and MODIS are remote sensing instruments
flown on board what are commonly referred to as
POES type satellites. POES are Sun-synchronous,
polar orbiting, wide field of view, low
resolution (250 m to 4-km) satellites that are
capable of view the entire earth within a one or
two day period Examples of POES Satellites are
  • NOAA series began in 1979 with NOAA-6 and
    continues today with NOAA-16
  • Defense Meteorological Satellite Program (DMSP),
    which began in the 1960s with more modern
    instruments being deployed in the 1980s to
    present.
  • European Remote Sensing Satellites (ERS), began
    in 1981 with ERS-1 and continuing with ERS-2,
    which was launched in 1995.
  • NASAs Earth Observation System, began with the
    launch of Terra (EOS/AM-1) in December 1999 and
    which will continue with the launch of Aqua
    (EOS/PM-1) in 2001
  • Other satellites include the FY series from
    china and SeaWiFS, as well as non sun-synchronous
    satellites such as the Tropical Rainfall
    Measuring Mission (TRMM)

13
Purpose of POES
POES satellites were originally designed for
meteorological purposes.
  • POES daily global coverage enables the
    monitoring of clouds and other atmospheric
    meteorological variables that required diurnal
    data frequency.
  • POES data are used in conjunction with data from
    Geostationary Satellites (GEOS), which do not
    provide global coverage, to monitor the
    atmosphere.

In the mid 1980s data from the AVHRR instrument,
flown on the NOAA series of satellites, began to
be used for monitoring vegetation.
  • This was partially a reaction to the high cost
    of data from satellites such as LandSat and SPOT,
    which are specifically designed to study the land
    surface.
  • In contrast data from the NOAA series as well as
    NASAs EOS series are free.
  • They also provided data at a temporal frequency
    and spatial coverage where Global and regional
    vegetation dynamic studies can be performed.
  • Compositing methods have been developed that
    remove cloud cover, enabling the continuous
    monitoring of vegetation and other land surface
    variables, such as temperature, on a bi-weekly
    bases.

14
Instrument specifics
MODIS is flown on NASA, Terra Aqua launches
1999, 2001 705 km polar orbit, sun synchronous
descending (1030 a.m.) ascending (130 p.m.),
providing 1 to 2 day global coverage Sensor
Characteristics 2300 km (cross track)
and 2000 km (5 min. granule along track) 36
spectral bands ranging from 0.41 to 14.385
µm Spatial resolutions 250 m (bands 1 - 2) 500 m
(bands 3 - 7) 1000 m (bands 8 - 36)
AVHRR is flown on the NOAA series of
satellite Launch date 6/23/81 (NOAA-7),
12/12/84 (NOAA-9), 9/24/88 (NOAA-11), 12/30/94
(NOAA-14) Sun synchronous, near polar (98.8
degrees) at 833 km Ascending (14.30 (NOAA-7),
14.20 (NOAA-9), 13.30 (NOAA-11), 13.30
(NOAA-14) LST), providing 1 day global
coverage Sensor Characteristics 2700-km (cross
track) and 102 minutes orbit period 5 spectral
bands ranging from 0.58 to 12.5 µm Spatial
resolutions 1.1 km for Local Area Coverage
(LAC) and High Resolution Picture
Transmission (HRPT) 4 km for Global Area
Coverage (GAC)
15
Utilization of AVHRR and MODIS data to Monitor
Vegetation and Other Land Surface Variables
  • The 2000-km cross track swath of these
    instruments, compared to Landsat-7 ETM 185-km
    swath (16-day repeat cycle), enable data to be
    collected over the same region on a 1 or 2 day
    temporal frequency.
  • The data is also continually collected for the
    entire globe, compared to higher resolution
    satellite data, such as Landsat and SPOT, which
    selectively choose images.
  • As stated previously the higher temporal
    frequency of the data enables compositing
    methods to be used that remove cloud cover,
    resulting in the ability to produce cloud free
    land surface parameters on a bi-weekly temporal
    frequency.
  • This gives VAccess the opportunity to provide
    state wide land surface products, supplying
    information on the condition of vegetation as
    well as other environmental variables, on a
    bi-weekly bases.
  • This will provide base information to perform a
    wide variety of environmental studies.

16
A simple example of a land surface product that
can be produced on a bi-weekly bases is the
Normalized Difference Vegetation Index (NDVI)
  • NDVI is derived from the red and near infrared
    channels on
  • satellite instruments such as AVHRR and MODIS

NDVI Rch2 - Rch1/Rch2 Rch1
where Rch1 is the land surface reflectance in the
visible wavelengths (580 to 680 nanometers) and
Rch2 is the land surface reflectance in the
infrared wavelengths (725 to 1000 nanometers)
  • NDVI is Widely Used for Monitoring Global
    Vegetation
  • Dynamics having been Applied to

1) Studies of the Global Carbon Cycle 2) Modeling
the Hydrological Cycle 3) Crop monitoring 4) UNs
Famine Early Warning System 5) Producing a wide
variety of other vegetation products including
Net Primary Production (NPP) Leaf Area Index
(LAI)
17
Example of NDVI Image Derived from AVHRR
10-day Composite AVHRR NDVI Image of Virginia,
July 1-10, 1992
18
AVHRR VS. MODIS
  • Both AVHRR and MODIS can be used to produce land
    surface variables such as
  • Surface Temperature, Land Cover, Thermal
    Anomalies/Fire, Leaf Area Index, Net Primary
    Production and Vegetation Cover
  • MODIS is a more advanced instrument than AVHRR,
    and as a result can produce more accurate
    products.
  • However it currently has less than two years of
    data available, this limits its use in vegetation
    dynamic studies.
  • AVHRR has 20 years of data, stretching over
    multiple satellites
  • Efforts such as the NOAA/NASA Pathfinder project
    have produced calibrated data sets over this
    entire time period, providing an extremely
    valuable historical record of the environment.
  • The historical record also permits the
    development of anomaly products, which compare
    the entire 20 year time period with a specific
    time, showing anomalies from the mean.

19
Comparison Between MODIS and AVHRR
The MODIS 250m-resolution multi-spectral
observations clearly discriminate different
types of vegetation and urban areas in this
image. The subsets show MODIS near-infrared
band 2 (859nm) at 250m resolution (top right)
and the corresponding NOAA14 AVHRR 1km band 2
(bottom right) over the Choptank River and the
Cambridge area, in the Delmarva Peninsula. The
improved spatial resolution of MODIS data over
the heritage AVHRR data is apparent.
20
AVHRR Products
Three variations of AVHRR products will be
produced
1) Products produced from the NOAA/NASA
Pathfinder AVHRR LandPAL 8-km data set, covering
the time period from 1981 to the present.
  • The PAL data set has been calibrated over the
    entire temporal range of AVHRR and mapped to a
    standard projection.
  • The daily data has been reconfigured into
    regional time-series files that will allow new
    compositing methods to be utilized, improving
    cloud removal, resulting in more accurate
    vegetation parameters such as LAI.

2) Products produced, from level-1b data at the
original 4-km GAC resolution, covering a shorter
time period. 3) Prototype products produced from
HRPT data collected at GMU
The products will focus on vegetation and include
NDVI, LAI, Land Cover Change and fraction of
Absorbed Photosynthetically Active radiation
(fAPAR) Experimental products including Land
Surface Temperature, Vegetation Anomalies and Net
Primary Production (NPP) will also be explored.
21
MODIS Products
A wide variety of high level products are
currently being produced from MODIS data
including
Surface Temperature, Land Cover, Thermal
Anomalies/Fire, Leaf Area Index, Net Primary
Production and Vegetation Cover
These products will be acquired for VAccess and
technical issues such as map re-projection will
be dealt with. Standard MODIS products that may
be useful in monitoring atmospheric pollution and
the Chesapeake bay will also be examined. Data
obtained through MODISs Direct Broadcast system
will be aquired.
22
Conclusion
Producing and acquiring land surface data sets
derived from POES satellites, will enable VAccess
to provide state wide products, for the
Commonwealth of Virginia, on a bi-weekly
bases. By doing this VAccess will provide base
products that can be utilized in a wide variety
of Environmental studies and monitoring efforts
including
1) Forest and Agricultural monitoring 2)
Non-point Pollution runoff Monitoring 3) Air
Quality studies 4) Wetland inventories 5) ...
23
Hyperspectral Imagery (HSI)Technology
VAccess HSI Project GMU/SCS/CEOSR Dr. Richard
B. Gomez
24
Hyperspectral Imagery
  • Data of the same scene collected simultaneously
    from hundreds of spectral bands, and registered
    on a single format.
  • A spectral band is a portion of the
    electromagnetic spectrum over which a sensor
    detects and measures scene reflections or
    emissions.

25
Reflected and Emitted Energy
UV
BLUE
GREEN
RED
NIR
SWIR
MWIR
LWIR
What you see is not what you get!
26
Pushbroom Hyperspectral Sensing

Pixel Spectrum
Flight Line
Intensity
Single Pixel
Wavelength
Spatial Pixels
Spectral Bands
Single Sensor Frame
Series of Sensor Frames
27
AISA Hyperspectral System
Airborne Hyperspectral Systems
28
Data Space Representations
  • Spectral Signatures - Physical Basis for Response
  • N-Dimensional Space - For Use in Pattern Analysis

29
Oil Spill Program Objectives
  • A well-managed oil spill response for the
    Patuxent River in the Chesapeake Bay area serves
    to
  • Protect human life
  • Develop mitigation processes
  • Identify vulnerable coastal locations before a
    spill happens (reduces the environmental
    consequences of both spills and cleanup efforts)
  • Establish protection priorities and identify
    cleanup strategies

30
Dr. George Taylor
31
Remote Sensing and the Environmental Sciences
  • Goal Demonstrate and encourage the application
    of remote sensing technology to pressing and
    emerging issues in the environmental sciences and
    policy
  • Multiple Media
  • Upland landscapes (e.g., agriculture, forestry,
    brownfields)
  • Rivers, Streams and Reservoirs
  • Estuaries and Wetlands
  • Bay and Near-Coastal Waters
  • Atmosphere (air quality)
  • Integrated and regional systems (e.g.,
    urban-suburban-rural systems with multiple
    landscape types)

32
Premiere Issues in the Environmental Sciences
  • Wetland ecology and management
  • Contaminants (organic and inorganic) in soil,
    surface water, subsurface, and plant/animal
  • Restoration/remediation of contaminated sites
  • Air quality (e.g., nitrogen, ozone, PM)
  • Stress detection and management in managed (e.g.,
    forests) and more natural stands of vegetation
  • Invasive species monitoring and management
  • Ecological risk assessment and management

33
Demonstration Scenarios
  • Wetland ecology and management
  • Atmospheric nitrogen deposition and
    eutrophication in the Chesapeake Bay
  • Monitoring contaminants in terrestrial landscapes
  • Stress detection in plant canopies

34
Ruixin Yang
35
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

36
VAccess Hardware Architecture
GIS Lab
Application Servers
VPN Solution
DB Server
VPN Solution
Programming
Data Sets
Mail Server
Filer
Temp Data Storage
FTP Server
Web Server
Partner Alpha
Partner Beta
AVHRR Ground Station
Key GMU-Partners Software Hardware
37
Software and IT components
  • 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/specific)
  • 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
  •         WMT prototype (International standard)
  • Metadata access

38
VAccess System Architecture
Industry User
Partner User
Student or Educational User
GMU User
INet Client Side
Middleware for Search and Browse
Local User
Local user
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
39
Virginia Access to Remote Sensing Data - Roles
of GIS
These data are Mostly in GIS Formats. GIS can
provide an Integrated environment to Bring
together These data RS data.

Spatial Analysis statistical Capabilities in
GIS
Community Server
Collaboration Infrastructure

Lo-Cost Regional Data
Prototyping Applications for VIRGINIA ACCESS
Application DataBases
Education Training

Modules on Integrating GIS/RS analysis
HSI Signature Library

Global RS Datasets

Some RS data Are available In GIS formats
Radars SAR NextRad

Key GMU Non-GMU
DEM and Topo data Are handled Efficiently
by Raster-based GIS
People
Process
Data
HW/SW
HW/SW
40
Hank Wolf
41
State of Virginia and the Use of Remote Sensing
Data
GMU ODU JMU VT UVA WM VSGC Hampton
42
VAccess Process Overview
Technical Advisory Committee Advise re
High-Level Priorities, Plans, Needs, Emphasis
Areas
  • Application Scenario Examples
  • Nitrogen, Contaminants Vegetation Stress
  • Water Quality Wetland Assessment
  • Agriculture Forestry Resource Management
  • Oil Spill Analysis and Mitigation
  • Natural Hazard Monitoring Prediction
  • Analysis Techniques for Virginia Hazards
  • Landscape Epidemiology
  • Mosquito-borne Illnesses
  • RS Data Sets
  • H S I - SAR
  • MODIS - AVHRR
  • LandSat - MISR
  • IKONOS
  • Other NASA Data
  • Buy Products

Subset Apply To
  • Building Infrastructure
  • Center Architecture
  • Functional Architecture
  • Data Analysis/Access
  • GIS
  • HSI Library/Access
  • Direct Broadcast Reception
  • a. User Education Awareness
  • -RS Algorithms, Tools, H S I
  • -Data Visualization Test Bed
  • -GIS/RS Tutorial
  • Natural Resources Tutorial

b. Future Workforce Training Hardware IR
Atmospheric Sensors Receiving Stations
Software Tools Training
Selected Prototypes User Feedback
43
Proposed Significant Project Activity Process
Subcontracts with VAccess Team
Contract with SSC
Activity Baseline
P.I.
Priority Activity Listing Planned
Active Completed
Technical Advisory Committee
Ranked Selection Criteria - Regulatory -
Programmatic - Decision Support - Legislative
Factfinding
PI Approval
Emphasis Areas Priorities
Proposed Activity Plan Objectives
Design Expected Results Schedule Costs Metrics
Map of RS Data To TAC Priorities
VAccess Team Scenarios Inputs
44
VIRGINIA ACCESS Project Component Relationships
Technical Advisory Committee Priority Definition
Emphasis Area Criteria Data/Products Validation
P.I.
Research Applications Goals Objectives Data
Needs Interfaces Expected Outputs
Approved Activity
Education Training
Data Earth Observing, Regional High
Resolution RS Subsets Data Attributes Data
Files Storage Sites Access Techniques
Design Requirements
Implementation Concepts
Access Protocols Installation Requirements Access
Requirements Hardware/Software Standards Data
Access/Catalog FTP Sites Distributed Access
Analysis Data Search
Prototype(s)
Stakeholder Feedback
45
Emphasis Areas Priorities will
Drive Implementation Completion
Virginia Access to Remote Sensing Data - Concept
and Examples
Special Capability Users
Community Server
Algorithms Statistical Tools Protocol
Data Metadata Files
Collaboration Infrastructure
Topography Maps Road Maps Demographic Data
Low-Cost Regional Data
Prototyping Applications for VIRGINIA ACCESS
Application DataBases
Education Training
Wetlands Data Land Classifications Vegetation
Graduate Courses Certificate Courses Distance
Learning Course Materials Instructor
List Schedule Sites
HSI Signature Library
Vegetation Structural Materials Roadway
Materials Sources AVIRIS, EO-1, In Situ
Global RS Datasets
Landsat 7 AVHRR MODIS ASTER TRMM SeaWiFS GOES MISR
SSM/I
Radars SAR NextRad
DEM Surface Objects Foliage Penetration Images
Prototype Examples For TAC Input
GMU Non-GMU
Key
Edu
HW/SW
Data
46
VAccess Innovation Pipeline Concept
Number Hours Concept Creation 100
1 Concept Refinement 15 5 Proof of
Concept 4 40 Prototype Development
2 500 Transfer to Provider 1 TBD
VAccess
Keep the Innovation Pipeline Full Keep Users
Involved Keep the Science Technology Real Keep
Nurturing the Later Steps
VAccess, Commonwealth Innovation Engine
47
VAccess First Year Phases
Start Up and Activity Processes Data Sub Setting
Scenario Refinement Education Training
Infrastructure Evolution Prototype Refinement
User Requirement Validation
48
GMU ODU JMU VT UVA WM VSGC Hampton
49
VAccess Team Projects
ODU RS Applications in Landscape
Epidemiology JMU Visualization Test Bed
Software for Shenandoah Valley Hampton
Advanced Analysis Techniques for RS
Data VSGC Leveraging a State-wide
Network VIMS Development of an Interactive I-Net
GIS/RS Tutorial VT Natural resources
Applications of RS Related Geospatial
Information Technologies UVA Deployment of an IR
Atmospheric Sensor
50
Thomas Allen
51
Applied Research in Mosquito-Borne Disease
Prevention
  • Tom Allen
  • Old Dominion University

52
Mosquito Control and Disease Surveillance
  • Arboviral and vector-borne disease surveillance
  • Encephalitides (EEE, LaCrosse, WNV)
  • Hantaviruses, Dengue Fever
  • Aedes albopictus and other arboviral vector spp.
  • Field-based surveillance and control
  • Mosquito light traps
  • Breeding/pool samples
  • Chicken flocks

53
Asian Tiger Mosquito Introduction Diffusion
54
Pilot Research
  • CDC, NC State, ODU, N.C. and V.A. Public Health
    Depts.
  • Identification of breeding Hot-Spots
  • Implementation of Integrated Pest Management
    (IPM)
  • NCSU Coop. Extension funding 2000-2001
  • Cooperators

55
Collaboration
  • Clarke Mosquito Control
  • Valent Biosciences
  • US Air Force C-130s (Wright-Patterson AFB, OH)
  • USMCAS Cherry Point, NC

56
Approach
  • Building multi-temporal time series of Landsat
    TM, ETM, and DOQQ imagery
  • Statistical and cartographic modeling of mosquito
    populations
  • Tasseled cap transformation
  • Multitemporal reflectance trajectories/CVA
  • Lagged response and two-stage multivariable ANOVA
  • GIS and logistic models with and without spatial
    dependence
  • Training vector control specialists in ArcGIS,
    Erdas, and Epi-Info
  • Develop applications for desktop GIS to improve
    mosquito control

57
IPM Benefits
  • Improved human health protection
  • Lower cost to local government
  • Expanded private-sector services
  • Pest management and controls
  • RD for improved IPM (e.g., larvicides)
  • Expanded services (rapid assessment and controls)

58
Public Sector Benefits
  • Improved efficiency and technology in local
    government (vector control)
  • Lower costs for improved mosquito control
  • Dissemination of RS in tandem with GIS and IT
    applications to public health

59
Technical Needs
  • Landsat TM/ETM archive
  • 6-10 scenes per season (t1-tn)
  • Phenology and event-driven acquisition
  • High spatial resolution imagery
  • Discrete image interpretation (ditches,
    drainages, other breeding sites)
  • Ikonos, SPOT, DOQQ
  • SAR and/or LIDAR
  • DEMs
  • Census TIGER 2000

60
Outreach
  • Educational materials (web and course materials)
  • Higher ed. and public end-users
  • Workshop
  • Collaboration with state agencies and/or local,
    regional and national Mosquito Control
    Associations

61
James Barnes
62
NASA RISE
  • Dr. James L. Barnes
  • Director

63
Technical Approach
  • As applied to Virginia and Chesapeake Bay region,
    the main objectives of NASA RISEs remote sensing
    focus are to
  • begin filling the void in understanding how
    digital geo-information technology can support
    decisionmaking functions of data and information
    at the local, state and regional levels,
  • help studentsat Virginia colleges make the
    transition from being designers of products to
    designers of information using knowledge-based
    thinking and decision-support tools, and
  • consider how geo-information technology applied
    to regional decision-support interacts with the
    social functions of information and data and the
    social context of science and technology use.

64
Tasks and Milestones
  • To establish a digital, regional, visualization
    test-bed that serves as a nucleating laboratory
    for community-based science and technology
    problem-solving.
  • Identify technologies, equipment, software and
    educational activities.
  • Identify partners and usage of data.
  • Define educational products and training.
  • Increase server and computing capability.
  • Expand technology infrastructure.

65
Tasks and Milestones Continued
  • To apply EyeSpyTM visualization software analysis
    tools for studying Earth environments in the
    Shenandoah Valley.
  • Identify technologies and educational activities
    most appropriate for EyeSpyTM visualization
    software.
  • Identify partners and usage of data.
  • Identify regional applications and modeling.
  • Define products and educational training.

66
Tasks and Milestones Continued
  • To develop 3-D virtual environments fly-bys for
    technology economic development in the Shenandoah
    Valley.
  • Identify regional applications and modeling.
  • Identify partners and usage of data.
  • Purchase imagery.
  • Define educational training.

67
Tasks and Milestones Continued
  • To prototype integration of emerging technologies
    for community-based decision making.
  • Data mining.
  • GIS.
  • Web-based databases.
  • Distance learning.
  • Define educational training.

68
AXS Technologies, Inc.EyeSpyTM Visualization
Testbed
  • EyeSpy allows end users to extract close-ups
    from, zoom-in on, and pan through high-resolution
    images over the web.
  • EyeSpy uses patented data striping and pipelining
    technology that delivers images to a user's
    browser in the blink of an eye.
  • http//www.axs-tech.com/index_green.php
  • Source http//www.axs-tech.com/html/products/eyes
    py/index.html

69
Pat McCormick
70
VAccess Hampton Univ.Efforts
  • M. Patrick McCormick
  • Prof. Co-Director
  • Center for Atmospheric Sciences

71
Tasks
  • As part of the Virginia State Virtual Remote
    Sensing Center Consortium (VSVRSCC) team, at a
    minimum, HU will
  • Build relationships and collaborations with the
    USGS to find out their needs, interests, and
    requirements for information on global and
    regional volcanism and earthquakes
  • Enhance relationships and collaborations with the
    NWS to find out their needs, interests, and
    requirements for global and regional hurricane
    studies and tropical storms

72
Tasks cont.
  • Strengthen relationships and collaborations with
    the EPA and find out their needs, interests, and
    requirements for global and regional-scale air
    pollution due to trans-oceanic transport of dust
    and aerosol particles, and biomass burning
  • Incorporate distance learning support for all
    atmospheric science courses to all VSVRSCC
    members and partners
  • Teach undergraduate and graduate level
    atmospheric science courses

73
Technical Approach
  • HU will draw on its comprehensive expertise in
    atmospheric science and remote sensing to
  • Study advanced remote sensing systems required to
    address current problems in atmospheric
    chemistry, climate and environmental research
  • Develop the capability to perform image analysis
    of large satellite data sets for study of clouds,
    hurricanes, volcanoes, Earth-fault changes
    (before and after earthquakes), continental
    pollution plumes, effects of long-range transport
    of desert dust and other environmental phenomena

74
Technical Approach cont.
  • Apply these techniques to NASA data sets such as
    TERRA, AQUA, TRMM and LANDSAT
  • Produce posters of the image analysis for public
    and educational outreach.

75
Title What are the Long- and Short-term Regional
Impacts of a Hurricane?
Theme Hurricanes. Evolution and impacts are or
will be observed by MODIS, MISR, SeaWiFs, GOES,
ASTER, QuickSat and PICASSO
  • A suite of experiment images will be used to
    show the evolution of a hurricane and
    correlations among experiments, structure, and
    devastation.

Teasers Correlations between MISR, MODIS,
SeaWiFs and other experiments. - Scientific
relevance of data based on hurricane evolution
and effects on specific regions.
Generic Poster Layout
ASTER (or other) image anytime before landfall
LITE/PICASSOVertical Cross Section of Hurricane
MISR or MODIS
ASTER (or other) image after landfall.
Multi-orbit composite showing Hurricane swath
with QuickSat velocity vectors overlayed.
MISR or MODIS
76
Title Do Dust Storms in the Saharan Desert Have
Global Environmental Impacts?
Theme Dust storms in the Saharan region cause
global scale effects. Impacts are
or will be observed by MODIS, MISR, SeaWiFs, TOMS
and ASTER
  • A combination of experiment images will be used
    to show dust correlations
  • among experiments, dust indices, the Red Tide
    and coral reef changes.

Teasers Correlations between MISR, TOMS and
other experiments. Relevance of data based on
health and pollution effects.
Poster Layout
MISR Multi-orbit composite showing dust transport
MODIS
ASTER
TOMS
Coral
Aerosol Index
Red tide
77
Title Do Volcanoes Impact Climate and/or
Chemistry   Theme We will use ASTER, MISR,
MODIS and SAGE data to depict the impact of
volcanic eruptions on climate and
chemistry.   Teasers Violent eruptions result
in new particles in the Earths stratosphere
resulting in cooling of the surface and
reductions of ozone on a global
basis.   Poster Make-up MODIS images of an
eruption MISR stratospheric images of an
eruption (Nadir view shows eye) ASTER image(s)
of plumes and Mount St. Helens TOMS SO2
plumes SAM II / SAGE I/II stratospheric
optical depth record since1978 Photograph of
Pinatubo
ASTER image of volcanic plumes
MISR Stereo Image
Eruptions that create local/regional
environmental problems e.g. flooding, crop losses
Eruptions that have global impacts to
climate/O3 chemistry  
Stratospheric Aerosol Optical Depth
90N
0
  • Large volcanic eruptions warm the stratosphere
    and cool the Earths surface.
  • These volcanic particles act as sites for ozone
    chemistry and resultant losses.

SAM II/SAGE data
90S
1978
2000
ASTER Image 3D of Mount St. Helens
Photograh of Pinatubo
78
Metrics by Quarter
  • Complete proposal, organize effort and begin
    research.
  • Develop CAS courses for distance learning
  • Complete first educational and public outreach
    materials and website.
  • Make available images, analysis and data products
    for applications germane to Virginia.

79
Deliverables
  • In a timely fashion, HU will
  • Deliver data products to the USGS, NWS, EPA, and
    the VSVRSCC science team manager (STM)
  • Deliver image mock-ups for education and public
    outreach to the STM
  • Provide copies draft documents and progress
    reports to the STM

80
Mary Sandy
81
Virginia Space Grant Consortium Virginia
Access (VAccess) ProjectsMiddle Atlantic Remote
Sensing Information Access System (MARSIAS)
  • Presented by
  • Mary Sandy, Director
  • Virginia Space Grant Consortium
  • July 9, 2001

82
VSGC -- Part of the NASA National Space Grant
College and Fellowship Program
  • Initiated by Congress to provide seed money to
    the states through NASA to
  • Improve math, science, technology and engineering
    education at all levels (pre-college through post
    doctoral and faculty levels) to ensure a highly
    qualified national talent pool
  • Build aerospace-related, high technology research
    capabilities at Space Grant universities
  • Encourage partnerships among government, industry
    and academia
  • Foster public science literacy
  • The Virginia Space Grant Consortium received its
    designation from NASA in September 1989.

83
Consortium Members
  • College of William and Mary
  • Hampton University
  • Old Dominion University
  • University of Virginia
  • Virginia Polytechnic Institute and State
    University
  • NASA Langley Research Center
  • State Council of Higher Education for Virginia
  • Virginia Community College System
  • Virginia Department of Education
  • Mathematics and Science Center
  • Science Museum of Virginia
  • Virginia Air and Space Center
  • Virginias Center for Innovative Technology

84
VSGC Partnerships
  • The Consortium works with NASA, the Commonwealth
    of Virginia, industry and many other partners
    (more than 300 to date) to accomplish its goals.
  • Current NASA Space Grant award is 475,000 per
    year
  • In recent years, the VSGC has leveraged each NASA
    Space Grant dollar invested by 4 - 5 from
    other sources.

85
VSGC Remote Sensing Working Group History
  • A state-wide Remote Sensing Working Group
    comprised of Space Grant university faculty, NASA
    researchers, land user planners, Cooperative
    Extension personnel, civil engineers and natural
    resource managers with the goal of determining
    how we might work together to access and use
    remote sensing images of Virginia for economic
    development research and education.
  • VSGC fellowship and scholarship opportunities
    were opened to students to assist faculty in
    learning to manipulate data sets.
  • Speakers and a meeting at NASA Langley helped
    introduce Working Group members to upcoming
    funding opportunities, related resources as well
    as kinds of data available and how they might be
    used.
  • A science plan was formulated that embraced
    several areas of interest of the Working Group
    members. One of the strong areas of interest was
    the need for comprehensive watershed data which
    impacts economic development, environmental
    impact and land use planning.

86
VSGC Remote Sensing Working Group History
continued
  • The VSGC co-sponsored a Precision Agriculture
    Workshop and a Remote Sensing conference with
    Virginia Tech.
  • The VSGC sponsored attendance by faculty and VSGC
    staff at three national Space Grant remote
    sensing conferences.
  • A number of grants were submitted by group
    members. Two were funded
  • Wetlands Remote Sensing Grant from NASA Langley
    Research Center to VSGC with ODUs Tom Allen and
    George Oertel.
  • NASA/Mission to Planet Earth--Centers of
    Excellence in Applications of Remote Sensing to
    Regional and Global Integrated Environmental
    Assessments, ODU PIs Tom Allen and George
    Oertel.
  • Build on network established through Working
    Group.

87
Other Remote Sensing Activities
  • The VSGC has undertaken a number of K-12
    outreach/teacher training activities with
    relevance to Remote Sensing.
  • The VSGC is partnered with the University of
    Virginia for IR Sensor Research. This effort is
    being done at the University of Virginia (Gabriel
    Laufer and Houston Wood), funded in part by the
    VSGC, to develop and deploy an Infrared
    atmospheric sensor on an Orion sounding rocket to
    be launched from NASA Wallops.
  • The VSGCs Director, Mary Sandy, has prepared a
    white paper. Background Paper on the National
    Space Grant College and Fellowship Program and
    Extension Services for Practical Applications of
    NASA Technologies for Chief of Staff of the VA,
    HUD and Independent Agencies Subcommittee, U.S.
    House of Representatives.
  • The VSGC participated in two sounding rocket
    projects to measure atmospheric ozone. These
    missions were undertaken in partnership with the
    Colorado Space Grant Consortium. Under the NASA
    Student Launch Program, the VSGC has undertaken
    two student-managed Upper Atmospheric Research
    Balloon missions involving a number of university
    and industry partners.

88
GoalNASA Space Grant Extension Specialist in
Geospatial Technology
  • Partners
  • National Space Grant College and Fellowship
    Program
  • U.S. Department of Agriculture, Cooperative State
    Research, Education, and Extension Service
    (CSREES)
  • Goal
  • To meet needs of farmers, ranchers, planners
    and others involved in agriculture, natural
    resource management, and rural development. Join
    the missions of NASAs Office of Earth Science
    and Space Grant with the experience and
    infrastructure of the USDA CSREES.
  • Approach
  • Place a Geospatial Technology Specialist within
    CSREES at Virginia Tech to help meet their
    information needs, using the three Primary
    Geospatial Technologies
  • Remote Sensing
  • Geographic Information System (GIS)
  • Global Positioning System (GPS)

89
Virginia Space Grant Consortium Support of
VAccess/MARSIAS
  • As a partner in VAccess/MARSIAS, the Virginia
    Space Grant Consortium (VSGC) will provide staff,
    faculty members, students, administrative
    services and cost sharing through projects which
    provide education and awareness, future workforce
    training, products and services, and relevant
    educational and research experience involving
    VSGC member faculty and students.
  • Coordination of VAccess activities across member
    institutions participating under VSGC umbrella
  • Seek synergy among VSGC programs and projects and
    VAccess. Natural linkages will be encouraged.
    Strong interest in building VSGC ties to related
    State agencies.
  • Coordination of Space Grant research scholarships
    and fellowships and faculty funding for topics
    related to VAccess goals. Minimum of 15,000 in
    VSGC funding to be provided.

90


Virginia Space Grant Consortium Support of
VAccess/MARSIAS (continued)
  • Development of an Interactive Internet GIS/Remote
    Sensing Tutorial in partnership with Virginia
    Institute of Marine Science. VIMS Leads Dr.
    James Perry and Dr. Michael Newman. VAccess
    funding at 15,500 is allocated for a VSGC
    graduate fellow to develop the Interactive
    Internet GIS Remote Sensing Tutorial.
  • Natural Resources Applications of Remote Sensing
    and Related Geospatial Information Technologies
    Extending the Reach of the Virtual Center in
    partnership with Virginia Tech. Virginia Tech
    Lead Dr. Randy Wynne.
  • Deployment of an IR atmospheric sensor on the
    Orion Sounding Rocket in partnership with the
    University of Virginia. UVA Lead Dr. Gaby Laufer.

91


Virginia Space Grant Consortium Support of
VAccess/MARSIAS (continued)
  • One quarter of VSGC Research Program Managers
    time will be dedicated to development of
    oversight of remote sensing programs related to
    VAccess. Directors time will be contributed.
  • VSGC projects and activities tie to the following
    components of VAccess User Education and
    Awareness Future Workforce Training
    Applications Databases Global Remote Sensing
    Data Sets HIS Signature Library and
    Collaboration and Support Infrastructure.

92


Virginia Space Grant Consortium Support of
VAccess/MARSIAS (continued)
  • The proposed initiatives are consistent with
    VAccess goals of expanding the benefits of earth
    science research, technology, and remote sensing
    data to address a broad range of Virginia needs
    by
  • 1) building an enabling infrastructure for data
    downloads, collaborative exchanges and database
    generation, as well as information products
    derived from the above
  • 2) prototyping exchanges of data and information
    products for specific regulatory
    programmatic/campaign activities,
    decision-support and legislative fact finding
    efforts
  • 3) providing education and training to
    identified stakeholders in the areas of remote
    sensing and associated technologies and
  • 4) identifying and using commercial remote
    sensing data for the above through the NASA data
    buy program prototyping exchanges of data and
    information products of interest to federal,
    state, and private sector applications.

93
James Perry
94
Development of an Interactive Internet GIS/Remote
Sensing Tutorial
  • James E. Perry, PWS, Ph.D.
  • Dept. Coastal and Ocean Policy
  • College of William and Mary
  • Virginia Institute of Marine Science

95
Introduction
  • Geographic Information Systems are a powerful new
    tool that can be used with spatial and temporal
    life science data sets
  • can be used to produce simple maps
    (visualization) or
  • can be used to perform advanced statistical
    spatial and temporal analysis.

96
Problem With Current System
  • Equipment not available
  • upgrades often not installed
  • tutorials expensive to students
  • students find manufacturers on-line tutorial
    boring and not pertinent to all life sciences.

97
Potential Solution
  • Create user friendly on-line tutorial available
    to students from their own machines
  • tutorial will be free to anyone who wishes to use
    it
  • will use examples from Chesapeake Bay and other
    available Virginia data (emphasis on life
    sciences).

98
Proposal
  • Tutorial will be developed and tested by VIMS
    faculty and graduate students
  • tested and validated by outside team of GIS
    specialists and GIS neophytes
  • server will be located at VIMS and maintained by
    VIMSs ITN staff.

99
Add On Value
  • VIMS ITN staff will maintain and upgrade system
  • will be linked to our VIMS-CERSP remote sensing
    tutorial (already on-line)
  • computer and GIS experts will be available to
    answer students questions.
  • students will be able to create own data files.

100
Current Web Sites
  • www.vims.edu
  • http//www.vims.edu/rmap/cers/tutorial/

101
Randy Wynne
102
Natural Resources Applications of Remote Sensing
and Related Geospatial Information Technologies
Extending the Reach of the Virtual Center
  • Randolph H. Wynne

103
Overall Objective
  • To facilitate the early adoption of remote
    sensing and other geospatial information
    technologies by Virginias Agriculture and
    Natural Resources extension agents to improve
    decision support by natural resources
    stakeholders throughout the Commonwealth.
  • Stated another way, our goal is to train the
    trainers!

104
Background VCE
  • Virginia Cooperative Extension (VCE) is devoted
    to citizen education in the areas of agriculture,
    natural resources, and the environment. VCE has a
    large, statewide network of 105 county and/or
    city offices, and 117 field agents who work in
    the broad area of Agriculture and Natural
    Resources (ANR). VCE also has an additional 148
    field agents who work in the areas of Family and
    Consumer Sciences and 4H Youth Development.

105
Background VCE Mission
  • The mission of VCE is to enable people to
    improve their lives through an educational
    process that uses scientific knowledge focused on
    issues and needs.

106
Current Relevant VCE Activity
  • 4H agent training in GPS units available
    statewide
  • ArcIMS server managed by AHNR IT
  • Counties and municipalities are using remote
    sensing and GIS for planning extension agents
    are often behind the scenes in these efforts
  • Precision agriculture
  • FORSite (Forestry OutReach Site)

107
Other Virginia Tech Activity
  • Faculty Development Institute Spatial Track
    offered by OGIS faculty for the last three years
  • Significant remote sensing expertise and training
    facilities through CEARS
  • Significant GIS expertise through OGIS
  • Emphasis on algorithm and database development in
    an applied, disciplinary context
  • Strong linkages to VAccess, Virginia Space Grant
    Consortium, other universities, federal agencies

108
Precursors to Training
  • General training needs assessment in progress
  • Queries of successful programs in other states
    (e.g., Mississippi Georgia)
  • Trainings scheduled (December March)
  • Identification of attendees their project ideas
  • Introductory ESRI online courses (ArcGIS)
  • Agent-tailored data sets

109
Agent-Tailored Data Sets
  • Landsat TM subsets from 1998-2001 imagery
  • DRGs
  • Vector layers of roads, water bodies,
    administrative boundaries, etc.
  • Virginia GAP land cover maps
  • DCR watershed unit boundaries
  • Stream stations (DEQ sampling points, USGS
    stations, water intakes discharges)
  • DOF forest cover maps
  • NED DEMs
  • Soils from NRCS and DCR
  • Other remotely sensed data as needed and already
    available (two statewide SPOT acquisitions)

110
Training Objectives
  • Enable each extension agent to effectively
    incorporate GPS into their outreach programs
  • Provide each extension agent with their own copy
    of ArcGIS and major extensions (software costs
    represent in-kind support from VCE)
  • Enable each extension agent to utilize ArcGIS and
    major extensions to display, query, and analyze
    remotely-sensed and other spatial data
  • Facilitate individual projects in which extension
    agents can use their personalized data sets to
    concentrate on an activity that is best suited to
    their existing clients and outreach efforts

111
Expected Benefits (I)
  • Reaching out to VCE is vital to the ultimate
    success of the Virtual Center, as it will enable
    increased diffusion of remotely sensed data and,
    as or more important, the ability to manipulate
    and analyze the data in an applied, operational
    context. By concentrating first on
    early-adopters among the existing extension
    agents, this effort should have a multiplicative
    effect, as we are proposing to train the
    trainers in many respects.

112
Expected Benefits (II)
  • We recognize that the extension agents will by
    no means have all they need to know after the
    training, but they will be able to take home
    working knowledge coupled with a working data set
    that will help build the Commonwealths
    geospatial applications infrastructure. The
    training is also unique in that it recognizes
    that GIS software purveyors are best equipped to
    train users on the use of their software, while
    applications specialist are best qualified to
    address the particular geospatial needs of
    natural resource managers.

113
Gaby Laufer
114
UVA SUB-ORBITAL PAYLOAD PROJECT
  • By
  • Gabriel Laufer
  • University of Virginia

115
Objectives
  • Develop unique engineering educational experience
    that includes realistic engineering and research
    projects.
  • Develop experimental facilities and capabilities
    that allow at least one annual undergraduate sub
    orbital launch of remote-sensing experiment.

116
Partners
  • VSGC,
  • Litton PRC,
  • Orbital Sciences Corporation,
  • NASA WFF and LaRC,
  • VAccess, JMU, GMU, HU, ODU
  • Virginia Space Port Authority

117
Current System Components
  • TE cooled MCT IR sensor system,
  • Video camera/VCR recording,
  • 3 photo-diodes with RGB color filters,
  • System sensors (temperature, pressure, voltage),
  • On board data logger,
  • Telemetry (multiplexer transmitter)

118
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119
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120
Imaging and telemetry deck
Photodiodes and house keeping board
IR sensor system And data logger
Power deck
NSROC secondary payload
121
April 2001
122
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123
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124
Launch of single stage Orion carrying UVas
payload April 27, 2001
  • Payload weight 225 lb, apogee 155,510 ft, flight
    time 18 min.
  • Payload recovered successfully. Data obtained by
    telemetry and on-board recoding
  • Future launch will include spectral imaging
    (MODIS validation) and stratospheric methane.

125
Photodiode and IR Sensor Voltage Output
126
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127
One frame of the video image showing the
separated rocket motor
128
Results of work in progress
  • Demonstrated the entire system, including
    sensors, house-keeping, on-board recording,
    telemetry, deployments of shield, recovery,
  • Obtained data of IR sensor and RGB photo-diodes
    that are consistent with observations,
  • Images of the video camera correlate with system
    time base, photo-diode output, and provide
    moderate resolution even during fast spin,
  • Demonstrated operation of TE cooled MCT,
    tuning-fork chopper and DC-DC converters.

129
Summary Wrap Up
Action Items TAC Meeting Plans Project
Schedule
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