Integrating NASA Earth Science Enterprise Data into Global Agricultural Decision Support Systems A REASoN CAN Project Second Year Presentation and Demonstration July 21, 2005 Long Chiu, Paul Doraiswamy, Steven Kempler, Zhong Liu, William Teng, Robe

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Integrating NASA Earth Science Data into Global
Agricultural Decision Support Systems Data
Analysis and Visualization to Ensure Optimal Use
Joint Workshop on NASA Biodiversity,
Terrestrial Ecology, and Related Applied
SciencesAugust 22, 2006 Steve Kempler,
PISteven.J.Kempler_at_nasa.govNASA GSFC Earth
Science (GES) Data and Information Services
Center (DISC)withWilliam Teng (RSIS), Paul
Doraiswamy (USDA ARS), Zhong Liu (GMU), Long
Chiu (GMU), Dimitar Ouzounov (RSIS)Robert
Tetrault (USDA FAS), Leonard Milich (UN WFP)
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Table of Contents

• Project Synopsis
• Project Objectives, Accomplishments, and Sample
  Products
• Project Outreach
• Conclusions - Impacts, Outcomes

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Integrating NASA Earth Science Data into Global
Agricultural Decision Support SystemsObjectives

• Integrate relevant NASA Earth Science data into
  modeling and operational systems to enhance the
  accuracy and timely assessments of global
  agricultural crop conditions
• Provide NASA satellite data-based, operational
  solutions to the USDA FAS and UN WFP, by
  leveraging existing capabilities of these two
  user organizations and of the GES DISC

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Integrating NASA Earth Science Data into Global
Agricultural Decision Support Systems

• Partners
• USDA Agricultural Research Service (ARS)
• - Paul Doraiswamy
• USDA Foreign Agricultural Service (FAS)
• - Robert Tetrault
• UN World Food Programme (WFP)
• Leonard Milich
• Other Particulars
• This work is the result of funding from NASA
  REASoN Cooperative Agreement Notice (CAN)
  CAN-02-OES-01
• Commenced 11/03
• Program Manager Ed Sheffner

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Collaborator Roles

• NASA GSFC Earth Science (GES) Data and
  Information Services Center (DISC)
• Develop the Agricultural Information System (AIS)
  to provide specific NASA remote sensing,
  agriculture related products of interest to its
  partners
• USDA Agricultural Research Service (ARS)
• Develop new/improved crop model outputs, based on
  FAS and WFP requirements, using NASA supplied
  data products
• USDA Foreign Agricultural Service (FAS)
• Operational user of remote sensing data for
  global crop monitoring, decision support systems.
  
• UN World Food Programme (WFP)
• Operational user of remote sensing data for
  global crop monitoring, decision support systems.

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NASA Remote Sensing Data Requirements

• Multi-Satellite Precipitation Product (TRMM based
  - 3B42RT) - 10 Day Composite, binned at 0.25
  degree
• MODIS - 10 Day Composite, 250 m Surface
  Reflectance

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Project Activities

1. Develop agriculture-oriented hydrologic products
   based on TRMM and other satellites
2. Generate MODIS 250-m, 10-Day composite surface
   reflectance product
3. Develop agriculture-oriented land products based
   on MODIS and TRMM
4. Develop Agricultural Information System (AIS)
   based on GES DISCs Giovanni data exploration and
   analysis tool
5. Integrate NASA products into USDA/FAS Decision
   Support System
6. Integrate NASA products into UN/WFP Decision
   Support System

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Activity 1 Develop agriculture-oriented
hydrologic products

• Objectives
• Provide NASA precipitation products
• Evaluate precipitation products bias and error
  with regards to AFWA (Agrimet, currently used by
  FAS) and mesonet gauge analysis
• Evaluate and promote utility of new/potential
  products cumulative rainfall (departure,
  normalized departure) and 10 day rainfall for
  growing season

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Accomplishments

• Produced global 0.25 degree TRMM 3B42-V6, decadal
  accumulation, climatology, and percent-normal
• Monthly TRMM compares well with GPCC and Climate
  Division Gauge Analysis over OK (bias, departure
  and percent normal)
• Analysis over OK shows additional
  spatial/temporal information in TRMM to
  complement AFWA precipitation analysis,
  especially in other non-gauge areas

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Time Series of TRMM, GPCC and Climate Division
(CD) Data over OK
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Activity 2 Generate MODIS 250-m, 10-Day
composite surface reflectance product

• Objectives
• Generate MODIS 250-m surface reflectance product,
  as required, to be in phase with other FAS Crop
  Explorer products
• Evaluate new surface reflectance product bias
  and error with regards to same 8-Day composite
  product
• Facilitate on-line access to new products

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Accomplishments

• Completed development of 10-day MODIS Land
  Surface Reflectance product, based on a
  modification of the standard MODIS L3 8-day Land
  Surface Reflectance product (MOD_PR09A), written
  by Eric Vermote and Jim Ray of the MODIS Land
  Science Team.
• Two crop seasons worth of files were generated
  for comparison by USDA-ARS.
• NDVI was derived from the 10-day reflectance
  product and compared with the 8-day NDVI.
• NDVI curves show a general similarity between the
  two products, but the reason for the temporal
  differences needs additional investigation.
• 10-day NDVI curve tends to green up and senesce
  earlier than does the 8-day curve (See next
  slide)
• 10-day NDVI curve shows less variability than
  does the 8-day curve. Investigations into the
  implications of these results are needed.

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Comparison of 10-day and 8-day NDVI curves,
Oklahoma (USDA ARS)
Further analysis is needed for the proper use of
this 10-day product
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Activity 3 Develop agriculture-oriented products
based NASA data inputs

• Objectives
• Conduct field studies to validate crop yield
  simulation models and scale simulation for
  regional assessment using MODIS 8-day composite
  data
• Study areas Oklahoma, winter wheat
  (2003-04) Argentina, Corn (2004-2005)
• Study disaggregation of TRMM rainfall data to 1
  km resolution using the MODIS Thermal data
• Apply the TRMM rainfall data in crop yield
  simulation model and evaluate potential
  improvement in crop yield assessment
• Evaluate a MODIS 10-day product for crop yield
  simulations
• Provide FAS/PECAD validated models for their
  operational use

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Accomplishments

• Completed modeling of winter wheat yields for the
  Oklahoma study area and prepared a manuscript for
  submission to Photogrammetric Engineering and
  Remote Sensing.
• Completed analyses of all field data collected in
  Argentina.
• Developed algorithms to disaggregate TRMM
  0.25-degree grid data to a 1 km product using
  MODIS 1 km Thermal data
• Acquired (from the GES DISC) MODIS 8-day
  composite bands 1 and 2 reflectance data over the
  200 x 200 km2 study area. Retrieved the
  reflectance for each of the study fields.
• Used the SAIL radiative transfer model to derive
  leaf area index (LAI) from the MODIS data for
  each of the study fields. Completed model
  simulations of corn crop yields using the
  MODIS-derived LAI.
• Evaluated the use of TRMM derived data products
  and MODIS 10-day composite data in the crop yield
  model

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For Validation Only
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Results of Winter Wheat Studies in Oklahoma
Parameter Optimization using Modis data
Model
Flowchart
Flowchart
Wheat Mask
Soil Polygons
Mesonet Stations
Canadian and Kingfisher counties in Oklahoma
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Activity 4 Develop the Agricultural Information
System (AIS)

• Objectives
• Develop an information system (i.e., AIS) that
  easily locates desired data and provides quick
  visualizations of and access to the data for
  further analysis
• Ensure that the AIS serves general agricultural
  information users, operational users, and
  advanced users (through community input).
• Enhance GES DISC Giovanni data exploration and
  analysis tool to include NASA data relevant to
  agricultural applications

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Enhancements to Giovanni for AIS

• Precipitation anomalies generation
• Inter-comparison of precipitation products
• Customized plot features User-selectable
  features color bar, contour intervals,
  minimum/maximum, and ASCII output.
• Customized scripts - For operational users
• Additional precipitation and other
  agriculture-oriented data products (e.g., model
  prediction data).
• Integration with existing Open Geospatial
  Consortium (OGC)-compliant client To enable
  remote access of distributed data, thus
  potentially thus potentially greatly increasing
  the number of data products available to AIS
  users.

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Accomplishments
NASA GES DISC Agriculture Web Portalhttp//disc.g
sfc.nasa.gov/agriculture/index.shtml
NASA GES DISC Agricultural Information
System http//disc.gsfc.nasa.gov/agriculture/ais_s
um.shtml
Map Guide to Analysis of Current Precipitation
Conditions http//disc.gsfc.nasa. gov/agriculture/
ais_sup/current_ conditions.shtml
Agriculture Online Visualization and Analysis
System (AOVAS) http//agdisc.gsfc. nasa.gov/ Giova
nni/aovas/
Link to USDA FAS Crop Explorer http//www.pecad.
fas.usda.gov/ cropexplorer/ mpa_maps.cfm
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NASA GES DISC Agriculture Web Portal (page top)
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NASA GES DISC Agriculture Web Portal (page
bottom)
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AOVAS Analysis
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Accomplishments

• Newest feature of AIS -
• Current Precipitation Conditions
• Provides analyses of current conditions, based on
  the experimental near-real-time TRMM
  Multi-Satellite Precipitation Analysis (TMPA or
  3B42RT).
• Users can access continually updated maps of
  accumulated rainfall, rainfall anomaly, and
  percent of normal
• For various regions of the world
• For time periods ranging from 3-hourly to 90-day

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Current Condition Analysis
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Activity 5 Integrate NASA products into
USDA/FAS Decision Support System

• Objectives
• Provide NASA products that support the USDA/FAS
  Crop Explorer Decision Support System and
  analysis
• Provide easy, seamless access to NASA data
  through web interfaces familiar to FAS analysts
• Present NASA products to the FAS analysts,
  addressing product definitions, accuracy,
  relevance, and usability

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Accomplishments

• Completed the machine-to-machine, web service
  connection between the FAS Crop Explorer and
  Giovanni-Agriculture (AOVAS) in the FAS
  operational baseline.
• Paradigm Shift!
• Taking advantage of evolving technology, more
  efficient interactive data access directly from
  GES DISC archives was implemented, minimizing
  large data transfers to FAS (original concept).
• This significantly reduces cost of data transfer,
  and maintenance.
• FAS would thus ned to be concerned about data
  version changes, reprocessings, etc.
• Data is, indeed, just a click away
• Project products are made publicly visible,
  seamlessly, from within Crop Explorer.
• User clicking on a region of the world will
  access and retrieve from AOVAS the latest 10-day
  rainfall map
• Data derived from the TRMM Multi-Satellite
  Precipitation Analysis (TMPA) data produced by
  Dr. Robert Adler, TRMM Project Scientist.
• From any Crop Explorer Web page of a given
  region, a user can access and retrieve NASA TMPA
  maps for the same spatial region/time period as
  those of other Crop Explorer rainfall maps (e.g.,
  WMO, Air Force Weather Agency).

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NASA GES DISC Agriculture Web Portal (page
bottom)
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• Crop Explorer users would link to the AIS data
  through the Crop Explorer home page
• http//www.pecad.fas.usda.gov/cropexplorer/

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Activity 6 Integrate NASA products for UN/WFP
Crop Monitoring

• Objective
• Provide NASA products that supports UN/WFP crop
  monitoring and analysis

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Accomplishments

• Generated and delivered 504 maps (31 MB) for
  post-season summary, evaluation, and uncertainty
  analysis. These include
• Climatology (individual months and growing
  season) maps from GPCC, TRMM, and Willmott
• Difference maps of GPCC, TRMM, and Willmott
  climatology baseline products
• Percent of normal maps derived from TRMM and the
  three baseline climatology products
• Gini (index to measure rainfall evenness) and
  z-score (measuring statistical departure) maps
  derived from TRMM and the three baseline
  climatology products.
• Received from WFP long-term station observations
  from Asia and Africa to better estimate
  anomalies.
• WFP ENSO reports, based in large part on project
  results, have been sent in to WFP HQ, as well as
  used in presentations for donors.
• AOVAS has also been used by WFP operations.

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Supporting UN World Food Programme

• Provided customized maps and data for UN WFP El
  Nino Bulletins
• Post-event evaluation (e.g., data, methods, and
  strategies)
• Summary of operation for journal publication

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Project Outreach

• Participated in and/or presented project results
  at (FY06)
• CCSP Workshop, Nov. 2005
• AGU Fall Meeting, Dec. 2005
• ESIP Federation Winter Meeting, Jan. 2006
• AMS 2006 Conference
• ASPRS Annual Conference, May 2006
• ESIP Federation Summer Meeting, July 2006.
• Participated in SEEDS Reuse Working Group
  telecons.
• Discussed potential extension/adaptation of
  project results with other USDA organizations and
  government agencies, in support of their decision
  support systems.

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Related Publications

• Teng, W., et al. 2004 Integrating NASA Earth
  Science Enterprise (ESE) data into global
  agricultural decision support systems, ASPRS
  annual conference, May 23-28, 2004, Denver, CO
• Chiu, L., C. Lim, W. Teng, 2004 AIS development
  TRMM and Oklahoma Climate Division rain rates,
  Second TRMM International Conference, September
  2004, Nara, Japan.
• Chiu, L., Z. Liu, H. Rui, and W. Teng, 2006
  Tropical Rainfall Measuring Mission (TRMM) data
  and access tools, in Earth System Science Remote
  Sensing, J. Qu et al. (Eds.), Springer-Tsinghua
  University Pub.
• Chiu, L., D-B. Shin, J. Kwiatkowski, 2006
  Surface rain rate from TRMM satellite, in Earth
  System Science Remote Sensing, J. Qu et al.,
  (Eds.) Springer-Tsinghua University Pub.
• Chiu, L., Z. Liu, J. Vongsaard, S. Morain, A.
  Budge, P. Neville, and S. Bales., 2006
  Comparison of TRMM and Water District Rain Rates
  over New Mexico, Advances in Atmospheric
  Sciences, 23 (1), 1-13
• Chiu, L., C. Lim, Z. Liu, W. Teng, P. Doraiswamy,
  B. Akhmedov 2005 Comparison of daily rainfall
  from Multi-Satellite Precipitation and Air Force
  Weather Agency analyses over parts of Oklahoma
  and Argentina region for crop yield monitoring,
  IAMAS, August 1-11, 2005, Beijing, PRC

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Conclusions Impacts

• Developed required 10-day products (evaluation
  ongoing)
• Precipitation, bias analysis
• MODIS surface reflectance
• Completed validation of improved climate-based
  crop model for Oklahoma and Argentina
• Enhanced ARS crop model with NASA remote sensing
  products
• Announced NASA Agriculture portal for access to
  NASA agriculture-related data products
• Announced operational tools that allow decision
  makers (and all other users) quick data
  exploration, discovery, visualization, and access
  capabilities, not previously available.
• Integrated NASA products for operational use into
  FAS and WFP decision support systems
• Advanced information science by developing
  technology that makes data availability seamless,
  regardless of its actual physical location.
  Data is only a click away.

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Conclusions Outcomes - 1

• More accurate decisions can be made with the
  arrival of additional precipitation data inputs
• At USDA/FAS - Precipitation maps available to FAS
  analysts, through their Crop Explorer decision
  support system
• At UN/WFP - Precipitation maps have greatly
  increased WFP crop monitoring and analysis
  abilities
• Soliciting feedback from FAS analysts will be
  valuable for further collaboration
• Field analysis proves valuable on two fronts
• USDA/ARS - Validates and improves crop models
• NASA - In situ data, further validates remote
  sensing data
• Additional field data analysis is needed to
  better understand regional biases on global
  remote sensing datasets

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Conclusions Outcomes - 2

• Data validation valuable to ensuring NASA product
  precision
• Precipitation Products (NASA GES DISC)- Data
  comparisons lead to valuable bias analysis
• MODIS Surface Reflectance - 8 day/10 day
  comparisons valuable in understanding data
  binning behavior
• Further analysis needed to more accurately
  characterize biases.
• Further analysis needed to understand the effects
  of varying multi-day composites
• Implementing advanced information technology
• Made operational, quick and easy exploration
  tools for very fast data analysis and
  visualization Takes the burden away from each
  user having to implement their own
• Made operational, lastest NASA precipitation
  maps, gaining great usage
• Implemented seamless operational access to
  remote data
• Technology can be applied to, and otherwise
  reused by, other science and application users
• Technology can be reused by other data management
  systems

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Parting Thought

• The usage of NASA data for specific applications
  can be best understood through close
  coordination.
• How will the data be used e.g., strictly visual,
  for modeling?)
• How precise must the data be (i.e., science
  quality?)
• For some applications, global datasets need to be
  validated locally
• Thank you,
• The Integrated Team

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BACKUP SLIDES
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MPA Continuity

• Operational SSM/I on board DMSP (F13, F14, F15) ?
  Conical scanning Microwave Imager/Sounder (CMIS)
  on board NPOESS
• Aqua Advanced Microwave Scanning Radiometer
  (AMSR)
• Operational NOAA Advanced Microwave Sounding Unit
  (AMSU)
• Operational GOES IR
• TRMM ? possible extension to 2010
• Additional Research Satellite microwave Sensors
• MPA ? prototype GPM core product

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MODIS 10-Day Surface Reflectance Product
Development Description

• Minor modifications were introduced into the PCF
  file in order to accept 10/11 MODIS tiles as
  inputs. There was no change in the order of
  compositing of the pixels across days and orbits,
  i.e., compositing within orbits according to
  orbital coverage of the pixel and the priority of
  the pixel (the pixel's score), then compositing
  across orbits according to channel 3 reflectance.
• Input data are 10 days' worth of 250m, 500m, and
  1 km compact L2G data MODMGGAD, MOD09GQK,
  MOD09GHK, MOD09GST, MODPTHKM, MODPTQKM.
• Output files are MOD09A1 500m Land surface
  reflectance, MOD09Q1 250m Land surface
  reflectance, and MOD09A1C 5km Land surface
  reflectance.

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