ARSET NASA

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ARSETNASAs Applied Remote Sensing Education
and Training Program
Richard Kleidman Science Systems and
Applications, Inc. NASA Goddard Space Flight
Center Ana Prados Joint Center for Earth Systems
Technology (JCET) University of Maryland
Baltimore County
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NASA and Earth ScienceApplied Sciences Program
Applications to Decision Making Eight Thematic
Areas
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NASAs Applied Remote Sensing Education and
Training
Our Current Focus
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ARSET Program Motivation

• NASA data products are underutilized

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• Barriers to Remote Sensing Data Utilization
• Lack of knowledge.
• Too much information to digest.

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• Barriers to Remote Sensing Data Utilization
• Lack of knowledge.
• a) So much was promised at the beginning of
  the satellite era. What can the satellite data
  really do for us?

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Current Application Areas of NASA Remote Sensing
DataNot a comprehensive list

• Long Range Transport of air pollution (regional
  scale). Attainment is a combination of local and
  upwind sources

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Long Range Transport of Air Pollution
October 20, 2007
October 21, 2007
October 22, 2007
October 23, 2007
October 24, 2007
October 25, 2007
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Current Application Areas of NASA Remote Sensing
DataNot a comprehensive list

• Long Range Transport of air pollution (regional
  scale). Attainment is a combination of local and
  upwind sources
• Improve data coverage and knowledge of air
  pollution trends where monitor data are lacking
  (e.g. forecasting).

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Relating Satellite Column Measurements to Ground
Concentrations
June 13, 2008
Figure courtesy, A. Huff
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Current Application Areas of NASA Remote Sensing
DataNot a comprehensive list

• Long Range Transport of air pollution (regional
  scale). Attainment is a combination of local and
  upwind sources
• Improve data coverage and knowledge of air
  pollution trends where monitor data are lacking
  (e.g. forecasting).
• Exceptional Event analysis allows states to
  obtain an exclusion for a NAAQS exceedance

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Exceptional Event Submittals Long range
transport of air pollution Virginia, Maryland and
North Carolina
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Current Application Areas of NASA Remote Sensing
DataNot a comprehensive list

• Long Range Transport of air pollution (regional
  scale). Attainment is a combination of local and
  upwind sources
• Improve data coverage and knowledge of air
  pollution trends where monitor data are lacking
  (e.g. forecasting).
• Exceptional Event analysis allows states to
  obtain an exclusion for a NAAQS exceedance
• Trace Gas Emissions Inventories and regulatory
  effectiveness (U.S and China Coal Plants)

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Earth Satellite ObservationsAdvantages and
Limitations
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Earth Satellite ObservationsAdvantages and
Limitations
Air Quality/Pollution

• Advantages
• Adds value when combined with surface monitor and
  models
• Provides coverage where there are no ground
  monitors
• Synoptic and transboundary view (time and space)
• Visual appeal
• Qualitative assessments and indications of long
  range transport
• Emerging Application areas

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Earth Satellite ObservationsAdvantages and
Limitations
Air Quality/Pollution

• Limitations
• Lack of specificity about pollutants type
• Resolution and temporal scales sometimes too
  coarse
• Vertical distribution often unknown (sum over
  column of air)
• Satellite data cannot be used quantitatively for
  enforcement purposes such as for example to
  determine whether a region is in attainment or
  not (Hoff and Christopher 2009).

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NASAs Applied Remote Sensing Education and
Training
Aerosol Products
Trace Gas Products
Fire Products
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Applied Remote Sensing Education and
Training Workshops and materials are
designed to help overcome many of the barriers to
proper utilization of remote sensing data.
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Training Philosophy- at the heart of
facilitating proper data usage

• Training is the transmitting of experience not
  just knowledge.
• People learn best when they are actively engaged
  through hands-on activities.
• Training activities must be tailored to the
  target audience therefore trainers must have the
  skills and resources to be flexible.
• Workshops alone are insufficient to transmit the
  experience needed to build expertise and capacity.

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• Barriers to Remote Sensing Data Utilization
• Lack of knowledge.
• a) So much was promised at the
  beginning of the satellite era. What can the
  satellite data really do for us?
• b) I didnt know that so much data was
  available
• and/or that NASA data is free.

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Negotiating the maze of information overload

• Sources for MODIS atmospheric products
• Ladsweb NASA archive site (3 interfaces plus
  ftp)
• iCARE French CNES archive site
• LANCE NASA real time data
• Giovanni NASA on-line analysis tool (6
  different instances)
• NEO NASA Earth Observations

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Negotiating the maze information overload

• Sources for MODIS images
• MODIS Rapid Response
• NASAs Earth Observatory
• NASAs Visible Earth
• MODIS today
• MODIS-atmos website
• Naval Research Lab

Just one among many products!
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NASA Satellite Products for Air Quality
Applications

• Particulate Pollution (dust, haze, smoke)
• - Qualitative Visual imagery
• - Quantitative Column Products and
  vertical
• extinction profiles
• Fire Products Fire locations or hot
  spots
• Trace Gases
• - Quantitative Column Products
• - Vertical profiles mostly mid-troposphere

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• Barriers to Remote Sensing Data Utilization

• Too much information to digest.
• a) Too many new developments to keep
• track of them all.
• b) Too steep a learning curve.

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Barriers to NASA Data Utilization

• 3. Institutional prioritization, lack of
  man-power and needed technical expertise.
• 4. Access to research results
• - Policy-relevant research remains largely
  inaccessible beyond the relatively small research
  community
• - cost of journals
• - knowledge gaps about data sets and
  their application to air quality management
  activities

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Methodology- Our philosophy in practice

• Provide context for the overwhelming mass of
  satellite data.
• - lectures, comparison charts, and
  materials archive.

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• Directed Messing Around
• We use the benefit of our experience to create
  hands on exercises to facilitate directed
  exploration of the most pertinent sources of
  information for the needs of our audience.

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• An example of Directed Messing Around
• The MODIS-atmos site. The most important
  reference site for MODIS atmospheric products.

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A complete image archive of Aqua and Terra true
color images for all 5 minute granules as well as
samples of other types of images.
Brief descriptions of, and links to, important
tools for MODIS analysis. All tools listed on
this page are free.

• A searchable data base of many important articles
  related to MODIS
• Atmosphere products.
• ATBD (algorithm theoretical basis documents)
  available for download
• These are complete and very detailed descriptions
  of the algorithms
• used to create the MODIS level 2 products.
• Several Power Point presentations are also
  available for download.

Brief and complete descriptions of all the
Atmosphere products as well as processing and
other information.
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Training Philosophy

• Training is the transmitting of experience not
  just knowledge.

NASAs Giovanni is one of the most user friendly
on-line tools for remote sensing data
analysis. Its ease of use makes it extremely
useful and frequently cited. All data sets must
be well understood to draw proper conclusions.
We use our experience to stress the proper
understanding and use of remote sensing data.
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Evaluating Remote Sensing Data

• Or
• How to Avoid
• Making Great Discoveries by Misinterpreting Data

Richard Kleidman ARSET Applied Remote Sensing
Education and Training A project of NASA Applied
Sciences
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MODIS 1 x 1 Degree Data from the on-line Giovanni
tool
Aqua Daily Overpass 130 PM local time
Terra Daily Overpass 1030 AM local time
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Possible ways to interpret these differences

• Real world differences
• Differences due to other factors
• Sensor error
• Algorithm error
• Sampling error.

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Training Philosophy

• Training is the transmitting of experience not
  just knowledge.
• People learn best when they are actively engaged
  through hands-on activities.
• Training activities must be tailored to the
  target audience therefore trainers must have the
  skills and resources to be flexible.
• Workshops alone are insufficient to transmit the
  experience needed to build expertise and capacity.

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Methodology- Our philosophy in practice

• Provide context for the overwhelming mass of
  satellite data.
• - lectures, comparison charts, and
  materials archive.
• Hands-on activities to explore individual sources
  of data
• - Directed messing around
• Overview and Review
• - Bringing it all together with case
  studies.

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Case Studies and Hands-On Activities

• Air Quality Event Template with step-by-step
  instructions
• 1) Access to imagery
• 2) Access to meteorological, model or
  other information
• 3) Utilization of image analysis tools
• 4) Air Quality Assessment
• -Type of event smoke, dust ?
• -Where is the pollution coming from?
  
• -Potential health impacts

University of North Carolina, October 2009
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Visualization ToolsMay 16th, 2007 Global View
of Transported Dust and Regional Smoke
Smoke
Dust
Source NASA MODIS Giovanni Image on Google Earth
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Case Study Analysis
Image from one of the training Case Studies
showing MODIS fire locations and True Color
Imagery dust and smoke. Google imagery
provided by the NRL Fire Locating and Modeling of
Burning Emissions (Flambé) Program.
Image from one of the training Case Studies,
showing MODIS fire locations and modeled
pollution dust and smoke - from the NRL Fire
Locating and Modeling of Burning Emissions
(Flambe) Program, which incorporates NASA
Satellite real-time observations in its model
predictions.
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Who are we training ? Expertise

• Air Quality Managers and Regulators
• EPA, state and local regulatory agencies, US
  Forest Service
• Scientists/Technical Meteorologists, air quality
  forecasters and modelers, health scientists, AQ
  researchers
• Other/public project managers, reps. from
  health agencies, World Bank

• ANY Audience can span a large range in
  expertise
• - No background in remote sensing and
  little science background
• - No background in remote sensing and
  some science background
• - Introductory expertise with satellite
  data
• - Moderate expertise with satellite data

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Workshop Goals

• Teach appropriate use of remote sensing data
• Navigate the maze of information sources
• Collaborate with applied end-users to
• - Identify areas that can benefit
  from
• inclusion of remote sensing data
  
• - Plan future training activities

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Workshops

• Range from 1 day overview to 4 day in depth
  presentations.
• Provide a framework and structure that can be
  applied to other remote sensing products.
• - Focus on relatively few products.
• Work with target audience and sponsors to design
  content and length.

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Typical Content of Remote Sensing Workshops

• Basics of remote sensing instruments, orbits,
• product overview, data formats
• Critical Thinking of Remote Sensing Strengths
  and caveats in the data products, retrieval
  characteristics
• Visualization Tools online tools and
  visualization via
• Google Earth greatly improved access to NASA
  Earth
• Science Data !!
• Case Studies and Hands-on Activities

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Accomplishments

• Developed a set of re-usable instructional
  modules
• Conducted 16 national and international training
  activities reaching several hundred participants
  since January 2009.
• Built a project website that provides NASA Earth
  Science Data users and potential trainers with
  free access to air quality training modules
• Developed a Case Study
  Inventory
• Workshop Attendees
• Local, Regional Federal Policy-makers
• Air Quality Professionals and Managers
• Students and Researchers

7 SEAS Workshop, Singapore
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Training Schedule for 2011Slots are still
available ask about scheduling a training
Host Location Dates
Griffith University Gold Coast, Australia April 4 7, 2011
NASA ARSET Training for EPA Region 4 Appalachian State University North Carolina June 2011
Community Modeling and Analysis (CMAS) Chapel Hill, North Carolina Sept. - Oct. 2011
International Society of Exposure Science Pre-Conference Workshop Baltimore, Maryland October 23, 2011
Air and Waste Management Association Montreal, Canada November 2011
NASA ARSET Training for EPA Region 6 TBD Texas TBD October - December
California Air Resources Board (Basic and Advanced Courses) Sacramento, California December 2011
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Whats new in 2011 and beyond

• Application-specific training modules and
  workshops
• - Biomass burning and dust events
• - Satellite/model comparisons
• - Health (e.g. PM2.5)
• - Exceptional event case studies
  for EPA area 6.
• Expanded products and topics for inclusion
• - Aerosols CALIPSO, MISR, AIRS
• - Trace Gases
• - European Data Sets

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Acknowledgements

• Lawrence Friedl
• Director NASA Applied Sciences Program, for
  providing funding for past and ongoing NASA
  Satellite training activities

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For More Information

• Richard.Kleidman_at_nasa.gov
• Ana.I.Prados_at_nasa.gov

http//ARSET.GSFC.NASA.GOV
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Extras
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Approach
Van Donkelaar et al. relate satellite-based
measurements of aerosol optical depth to PM2.5
using a global chemical transport model
van Donkelaar et al., EHP, in press
Following Liu et al., 2004
Estimated PM2.5 ? t
Combined MODIS/MISR Aerosol Optical Depth
GEOS-Chem
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MODIS and MISR AOD
Mean t 2001-2006 at 0.1º x 0.1º

• MODIS AOD
• 1-2 days for global coverage
• Requires assumptions about surface reflectivity

MODIS
r 0.40 vs. in-situ PM2.5

• MISR AOD
• 6-9 days for global coverage
• Simultaneous surface reflectance and aerosol
  retrieval

MISR
r 0.54 vs. in-situ PM2.5
0 0.1 0.2 0.3
t unitless
van Donkelaar et. at.
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Satellite vs. ARONET Varies with surface type
July
MODIS
MISR
9 surface types, defined by monthly mean surface
albedo ratios,
evaluation against AERONET AOD
van Donkelaar et. at.
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Combining MODIS and MISR improves agreement with
PM2.5
0.3 0.25 0.2 0.15 0.1 0.05 0
t unitless
Combined MODIS/MISR r 0.63 (vs. in-situ PM2.5)
MISR r 0.54 (vs. in-situ PM2.5)
MODIS r 0.40 (vs. in-situ PM2.5)
van Donkelaar et. at.
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Global CTMs can directly relate PM2.5 to AOD
van Donkelaar et. at.
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Significant agreement with coincident ground
measurements over NA
r
MODIS t 0.40
MISR t 0.54
Combined t 0.63
Combined PM2.5 0.78
Annual Mean PM2.5 µg/m3 (2001-2006)
Satellite Derived
Satellite-Derived µg/m3
In-situ
In-situ PM2.5 µg/m3
van Donkelaar et. at.