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VAccess Team Meeting. First Meeting of VAccess Team 19 th Floor 301 East Byrd Street Virginia Economic Development Partnership Richmond, Virginia July 9, 2001. GMU ODU JMU VT UVA W&M VSGC Hampton. VAccess: A Virtual Remote Sensing Information Access Center

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Vaccess team meeting
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

W&M

VSGC

Hampton


VAccess: A Virtual Remote Sensing Information Access Center

for Regional Applications in the Commonwealth of Virginia

Menas Kafatos

CEOSR

GMU

ODU

JMU

VT

UVA

W&M

VSGC

Hampton

  • CEOSR URL: http://www.ceosr.gmu.edu

  • VAccess URL: http://www.VAccess.gmu.edu

  • July, 2001


    Va july vaccess discussions july 9 2001 10th 1
    VA julyVAccess Discussions - July 9, 200110th 1

    1:00PM Introduction to VAccess Menas Kafatos

    Introductions, Overview, Status of VAccess

    1:15PM Global EO Data for Regional Applications James McManus

    1:25PM H S I Technology, Algorithms and Applications Richard Gomez

    1:35PM Environmental Scenarios George Taylor

    1:45PM Infrastructure, GIS & Other Tools Ruixin Yang

    1:55PM VAccess Process Hank Wolf

    2:05PM Landscape Epedemiology Tom Allen

    2:25PM Visualization Testbed James Barnes

    2:45PM Advanced Analysis Techniques for RS Data Pat McCormick

    3:05PM Break

    GMU

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    Vaccess discussions july 9 2001
    VAccess Discussions - July 9, 2001

    3:20PM Virginia Space Grant Consortium Mary Sandy

    3:45PM Interactive Internet GIS/RS Tutorial James Perry

    4:05PM Natural Resources Applications Randy Wynne

    4:25PM IR Atmospheric Sensor Gaby Laufer

    4:45PM Summary: Action Items, TAC Meeting Plans, Schedule Menas Kafatos

    5:00PM End of Meeting

    5:30PM Optional Dinner Discussions of Any Open Issues

    GMU

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    Earth space remote sensing data systems in ceosr
    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 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 VAccess

    GMU

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    VAccess:Virtual 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

    W&M

    VSGC

    Hampton


    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

    W&M

    VSGC

    Hampton


    State of virginia and the use of remote sensing data
    State of Virginia and the Use of Remote Sensing Data

    GMU

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    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)

    • SPOT (from VDEP and other state agencies)

    • Ikonos (NASA Data Buy Program)

    • Ground Data

    • Variety of GIS and other products for complementing RS data


    The Utility of AVHRR and MODIS Time-series Data Applications

    in Remote Sensing Application Studies

    James McManus

    GMU

    July 9, 2001


    Introduction Applications

    The purpose of the talk is to explain how VAccess can utilize data from the

    • NOAA’s Advanced Very High Resolution Radiometer (AVHRR) and

    • NASA’s 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.


    Polar-Orbiting Operational Environmental Satellites (POES) Applications

    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 1960’s with more modern instruments being deployed in the 1980’s to present.

    • European Remote Sensing Satellites (ERS), began in 1981 with ERS-1 and continuing with ERS-2, which was launched in 1995.

    • NASA’s 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)


    Purpose of POES Applications

    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 1980’s 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 NASA’s 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.


    Instrument specifics Applications

    • MODIS is flown on NASA, Terra & Aqua

      • launches 1999, 2001

      • 705 km polar orbit, sun synchronous descending (10:30 a.m.) & ascending (1:30 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)


    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.


    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) UN’s Famine Early Warning System

    5) Producing a wide variety of other vegetation products including:

    Net Primary Production (NPP)

    Leaf Area Index (LAI)


    Example of NDVI Image Derived from AVHRR produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    10-day Composite AVHRR NDVI Image of Virginia, July 1-10, 1992


    AVHRR VS. MODIS produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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.


    Comparison Between MODIS and AVHRR produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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.


    AVHRR Products produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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.


    MODIS Products produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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 MODIS’s Direct Broadcast system will be aquired.


    Conclusion produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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) ...


    Hyperspectral imagery hsi technology

    VAccess produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    HSI

    Project

    GMU/SCS/CEOSR

    Dr. Richard B. Gomez

    Hyperspectral Imagery (HSI)Technology


    Hyperspectral imagery
    Hyperspectral produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)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.


    Reflected and emitted energy
    Reflected and Emitted Energy produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    UV

    BLUE

    GREEN

    RED

    NIR

    SWIR

    MWIR

    LWIR

    What you see is not whatyou get!


    Pushbroom Hyperspectral Sensing produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Pixel Spectrum

    Flight

    Line

    Intensity

    Single Pixel

    Wavelength

    Spatial

    Pixels

    Spectral Bands

    Single Sensor Frame

    Series of Sensor Frames


    AISA Hyperspectral System produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Airborne Hyperspectral Systems


    Data Space Representations produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • Image Space - Geographic Orientation

    • Spectral Signatures - Physical Basis for Response

    • N-Dimensional Space - For Use in Pattern Analysis


    Oil Spill Program Objectives produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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


    Dr george taylor
    Dr. George Taylor produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    Remote sensing and the environmental sciences
    Remote Sensing and the Environmental Sciences produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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)


    Premiere issues in the environmental sciences
    Premiere Issues in the Environmental Sciences produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Demonstration scenarios
    Demonstration Scenarios produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • Wetland ecology and management

    • Atmospheric nitrogen deposition and eutrophication in the Chesapeake Bay

    • Monitoring contaminants in terrestrial landscapes

    • Stress detection in plant canopies


    Ruixin yang
    Ruixin Yang produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    Information technology strategy
    INFORMATION TECHNOLOGY STRATEGY produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Vaccess hardware architecture
    VAccess Hardware Architecture produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    GIS Lab

    Application

    Servers

    DB Server

    VPN

    Solution

    VPN

    Solution

    Programming

    Mail Server

    Data Sets

    Filer

    Temp

    Data

    Storage

    FTP Server

    Web Server

    Partner

    Alpha

    Partner

    Beta

    AVHRR

    Ground

    Station

    Key

    GMU-Partners

    Software

    Hardware


    Software and it components
    Software and IT components produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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

      • ·Metadata ingesting/creating

      • ·DBMS

      • ·XML technology (DIMES)


    Vaccess system architecture
    VAccess System Architecture produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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

    Order via INet

    INet

    Server Side

    Processor(s)

    Foreign

    GMU

    Partners

    NASA

    NOAA

    Satellite

    Down Link

    For Tailored Databases


    Virginia access to remote sensing data roles of gis
    Virginia Access to Remote Sensing Data produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)- 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

    HW/SW

    Data

    HW/SW


    Hank wolf
    Hank Wolf produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    State of virginia and the use of remote sensing data1
    State of Virginia and the Use of Remote Sensing Data produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    GMU

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    Vaccess process overview

    Technical Advisory Committee produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Advise re: High-Level Priorities,

    Plans, Needs, & Emphasis Areas

    VAccess Process Overview

    • 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


    Proposed significant project activity process
    Proposed Significant Project Activity Process produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Subcontracts

    with

    VAccess Team

    Contract

    with

    SSC

    P.I.

    Activity

    Baseline

    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


    Virginia access project component relationships

    Technical Advisory Committee produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Priority Definition; Emphasis Area Criteria;

    Data/Products Validation

    P.I.

    VIRGINIA ACCESS Project Component Relationships

    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


    Emphasis Areas & produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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

    Global RS

    Datasets

    Vegetation

    Structural Materials

    Roadway Materials

    Sources – AVIRIS,

    EO-1, In Situ

    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


    Vaccess innovation pipeline concept
    VAccess & Innovation Pipeline Concept produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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


    Vaccess first year phases
    VAccess First Year Phases produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Start Up and Activity Processes

    Data Sub Setting

    Scenario Refinement

    Education & Training

    Infrastructure Evolution

    Prototype Refinement & User Requirement Validation


    GMU produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    ODU

    JMU

    VT

    UVA

    W&M

    VSGC

    Hampton


    Vaccess team projects
    VAccess Team Projects produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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


    Thomas allen
    Thomas Allen produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    Applied research in mosquito borne disease prevention

    Applied Research in Mosquito-Borne Disease Prevention produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Tom Allen

    Old Dominion University


    Mosquito control and disease surveillance
    Mosquito Control and Disease Surveillance produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Asian Tiger produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Mosquito

    Introduction

    & Diffusion


    Pilot research
    Pilot Research produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Collaboration
    Collaboration produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • Clarke Mosquito Control

    • Valent Biosciences

    • US Air Force C-130s (Wright-Patterson AFB, OH)

    • USMCAS Cherry Point, NC


    Approach
    Approach produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


  • Ipm benefits
    IPM Benefits produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • Improved human health protection

    • Lower cost to local government

    • Expanded private-sector services

      • Pest management and controls

      • R&D for improved IPM (e.g., larvicides)

      • Expanded services (rapid assessment and controls)


    Public sector benefits
    Public Sector Benefits produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Technical needs
    Technical Needs produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    Outreach
    Outreach produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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


    James barnes
    James Barnes produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    Nasa rise

    NASA RISE produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    Dr. James L. Barnes

    Director


    Technical approach
    Technical Approach produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • As applied to Virginia and Chesapeake Bay region, the main objectives of NASA RISE’s 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.


    Tasks and milestones
    Tasks and Milestones produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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.


    Tasks and milestones continued
    Tasks and Milestones Continued produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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.


    Tasks and milestones continued1
    Tasks and Milestones Continued produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • 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.


    Tasks and milestones continued2
    Tasks and Milestones Continued produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    • To prototype integration of emerging technologies for community-based decision making.

      • Data mining.

      • GIS.

      • Web-based databases.

      • Distance learning.

      • Define educational training.


    Axs technologies inc eyespy tm visualization testbed
    AXS Technologies, Inc. produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)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/eyespy/index.html


    Pat mccormick
    Pat McCormick produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)


    Vaccess hampton univ efforts

    VAccess: Hampton Univ.Efforts produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    M. Patrick McCormick

    Prof. & Co-Director

    Center for Atmospheric Sciences


    Tasks
    Tasks produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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


    Tasks cont
    Tasks cont produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI).

    • 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


    Technical approach1
    Technical Approach produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI)

    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


    Technical approach cont
    Technical Approach cont produced on a bi-weekly bases is the Normalized Difference Vegetation Index (NDVI).

    • 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.


    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


    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


    Title: Environmental Impacts? 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 Earth’s 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 Earth’s 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


    Metrics by quarter
    Metrics by Quarter Environmental Impacts?

    • 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.


    Deliverables
    Deliverables Environmental Impacts?

    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


    Mary sandy
    Mary Sandy Environmental Impacts?


    Virginia Space Grant Consortium Environmental Impacts?Virginia Access (VAccess) ProjectsMiddle Atlantic Remote Sensing Information Access System (MARSIAS)

    Presented by

    Mary Sandy, Director

    Virginia Space Grant Consortium

    July 9, 2001


    Vsgc part of the nasa national space grant college and fellowship program
    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.


    Consortium members
    Consortium Members Fellowship Program

    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

    Virginia’s Center for Innovative Technology


    Vsgc partnerships
    VSGC Partnerships Fellowship Program

    • 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.


    Vsgc remote sensing working group history
    VSGC Remote Sensing Working Group History Fellowship Program

    • 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.


    Vsgc remote sensing working group history continued
    VSGC Remote Sensing Working Group History Fellowship Programcontinued

    • 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 ODU’s 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 PI’s Tom Allen and George Oertel.

    • Build on network established through Working Group.


    Other remote sensing activities
    Other Remote Sensing Activities: Fellowship Program

    • 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 VSGC’s 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.


    Goal nasa space grant extension specialist in geospatial technology
    Goal Fellowship ProgramNASA 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 NASA’s 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)


  • Virginia space grant consortium support of vaccess marsias
    Virginia Space Grant Consortium Fellowship ProgramSupport 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.


    Virginia Space Grant Consortium Fellowship ProgramSupport 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.


    Virginia Space Grant Consortium Fellowship ProgramSupport of VAccess/MARSIAS(continued)

    • One quarter of VSGC Research Program Manager’s time will be dedicated to development of oversight of remote sensing programs related to VAccess. Director’s 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.


    Virginia Space Grant Consortium Fellowship ProgramSupport 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 associatedtechnologies; and

      4) identifying and using commercial remote sensing data for the above through the NASA data buy programprototyping exchanges of data and information products of interest to federal, state, and private sector applications.


    James perry
    James Perry Fellowship Program


    Development of an interactive internet gis remote sensing tutorial

    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


    Introduction
    Introduction Tutorial

    • 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.


    Problem with current system
    Problem With Current System Tutorial

    • 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.


    Potential solution
    Potential Solution Tutorial

    • 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).


    Proposal
    Proposal Tutorial

    • 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 VIMS’s ITN staff.


    Add on value
    Add On Value Tutorial

    • 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.


    Current web sites
    Current Web Sites Tutorial

    • www.vims.edu

    • http://www.vims.edu/rmap/cers/tutorial/


    Randy wynne
    Randy Wynne Tutorial


    Natural Resources Applications of Remote Sensing and Related Geospatial Information Technologies: Extending the Reach of the Virtual Center

    Randolph H. Wynne


    Overall objective
    Overall Objective Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • To facilitate the early adoption of remote sensing and other geospatial information technologies by Virginia’s 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!


    Background vce
    Background: VCE Geospatial Information Technologies: Extending the Reach of the Virtual Center

    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.


    Background vce mission
    Background: VCE Mission Geospatial Information Technologies: Extending the Reach of the Virtual Center

    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.


    Current relevant vce activity
    Current Relevant VCE Activity Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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)


    Other virginia tech activity
    Other Virginia Tech Activity Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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


    Precursors to training
    Precursors to Training Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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


    Agent tailored data sets
    Agent-Tailored Data Sets Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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)


    Training objectives
    Training Objectives Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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


    Expected benefits i
    Expected Benefits (I) Geospatial Information Technologies: Extending the Reach of the Virtual Center

    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.


    Expected benefits ii
    Expected Benefits (II) Geospatial Information Technologies: Extending the Reach of the Virtual Center

    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 Commonwealth’s 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.


    Gaby laufer
    Gaby Laufer Geospatial Information Technologies: Extending the Reach of the Virtual Center


    Uva sub orbital payload project

    UVA SUB-ORBITAL PAYLOAD PROJECT Geospatial Information Technologies: Extending the Reach of the Virtual Center

    By

    Gabriel Laufer

    University of Virginia


    Objectives
    Objectives Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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.


    Partners
    Partners Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • VSGC,

    • Litton PRC,

    • Orbital Sciences Corporation,

    • NASA WFF and LaRC,

    • VAccess, JMU, GMU, HU, ODU

    • Virginia Space Port Authority


    Current system components
    Current System Components Geospatial Information Technologies: Extending the Reach of the Virtual Center

    • 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)


    Imaging and telemetry deck Geospatial Information Technologies: Extending the Reach of the Virtual Center

    Photodiodes and house keeping

    board

    IR sensor system

    And data logger

    Power deck

    NSROC secondary payload


    April 2001 Geospatial Information Technologies: Extending the Reach of the Virtual Center


    Launch of single stage orion carrying uva s payload april 27 2001
    Launch of single stage Orion carrying UVa’s 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.




    Results of work in progress
    Results of work in progress motor

    • 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.


    Summary wrap up
    Summary & Wrap Up motor

    Action Items

    TAC Meeting Plans

    Project Schedule


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