1 / 26

Developing Earth Observations Requirements for Global Agricultural Monitoring

Developing Earth Observations Requirements for Global Agricultural Monitoring. Alyssa K. Whitcraft, Inbal Becker-Reshef, Chris O. Justice, & Eric F. Vermote AGU Fall Meeting – B33L 11 December 2013 San Francisco, CA. The G20 Initiative: GEOGLAM.

cicero
Download Presentation

Developing Earth Observations Requirements for Global Agricultural Monitoring

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Developing Earth Observations Requirements for Global Agricultural Monitoring Alyssa K. Whitcraft, Inbal Becker-Reshef, Chris O. Justice, & Eric F. Vermote AGU Fall Meeting – B33L 11 December 2013 San Francisco, CA

  2. The G20 Initiative: GEOGLAM • The G20 Cannes Summit (November 2011) Action Plan on Food Price Volatility and Agriculture • Reaffirmed GEOGLAM commitment at the 2012 G20 Los Cabos Declaration & in Agriculture Ministers Report

  3. 4. EO DATA COORDINATION 5. METHOD IMPROVEMENT through R&D coordination (JECAM) 6. Data, products and INFORMATION DISSEMINATION GEOGLAM Components Stakeholders Governments AMIS FAO

  4. GEOGLAM Component 4: Coordination of Earth Observations • Cropping systems are inherently diverse and dynamic • No single mission can meet the variety of EO requirements • Lack of current coordination for agriculture monitoring • Committee on Earth Observations Satellites (CEOS) collaborating with GEOGLAM to devise an acquisition strategy • First step: EARTH OBSERVATIONS REQUIREMENTS

  5. Key Components of EO Requirements • Where to image? • When to image? • How frequently to image? • At what spatial & spectral resolution [instrument type]? • ‘best-available’ cropland mask • Agricultural growing season calendars • ‘best-practices’ from agricultural monitoring community of practice

  6. WHY? (Agricultural Monitoring Application) WHEN AND HOW OFTEN? (Temporal) WHAT? (Spatial & Spectral) WHERE? Coarse (>100 m) Moderate (10-70 m) Fine (5-10 m) Very Fine (<5 m)

  7. Where to Image? Best Available Cropland Distribution Source: IIASA, Steffen Fritz et al. Beta Version 1

  8. Where to Image? Field Size (beta version) Source: Fritz et al., (IIASA) Based on interpolation of 50,000 GEOWIKI validation points

  9. When to Image?AgriculturalGrowing Season Calendars • Produced for Agricultural Areas from ten years (2001-2010) of 8-day 250m MODIS Terra Surface Reflectance (MOD09Q1) • Adjusted using strict QA bits • Converted to NDVI; aggregated to 0.5° (~56 km at Equator) based on “best available cropland masks” • Processed for “Phenological Transition Dates” (PTD) • For each growing season, 2001-2010:

  10. Phenological Transition Dates (2001-2010) from MODIS NDVI over Cropped Areas Kansas – Winter Wheat Area Median SOS: 289 (16 October) Median EOS: 153 (2 June) Indiana – Corn/Soybean Area Median SOS: 137 (17 May) Median EOS: 273 (30 September)

  11. Median Start of Season, 2001-2010

  12. Median End of Season, 2001-2010

  13. Median Growing Season Duration, 2001-2010

  14. Median SOS

  15. Median EOS

  16. GSCs vs. USDA-NASS Crop Progress for Corn (2001-2010) Yearly SOS & Percent Planted Yearly SOS & Percent Emerged Yearly EOS & Percent Harvested

  17. How Frequently?Requirements Table + Cloud Cover • Investigating cloud cover: • Over agricultural areas, throughout the agricultural growing season (AGS) • At a resolution/with an approach that is scalable to multiple swath widths (~11 km – 720 km) of fine and moderate (FTM) resolution sensors • Probability of a Clear View at 0.05˚ • Daily; 2000-2011 [Terra-AM] and 2002-2011 [Aqua-PM] • ≥1 cloudy 1 km pixel  cloudy 0.05° cell • “What is the probability that there is no cloud within a given 0.05° cell on a given day or during a certain portion of the year?” “Worst Case” Likely to over-estimate impacts of cloud cover on acquiring clear views

  18. How Frequently?Requirements Table + Cloud Cover

  19. Where the Crops Are Terra (AM) – Western Terra (AM) – Eastern Probability of a Cloud Free Clear View at 0.05˚ Mean for each 1 degree of latitude

  20. AM – PM (Terra – Aqua) Morning acquisitions are less impacted by clouds than are Afternoon acquisitions Western Hemisphere Eastern Hemisphere

  21. How frequently to Image?Revisit Time Required For an 8 Day Clear View Incorporates Cropland Mask, Growing Season Calendar, and Clear View Probability

  22. Observation Capabilities • Show the table – perhaps 1 or 2 overpass analyses • Do this to establish why you are going to show 4 day repeat [attainable with a number of mission combinations]

  23. How Frequently? - Microwave • Highlight the areas for which microwave imagery are necessary

  24. Future Research • Refining growing season calendars • Crop specific cropland phenology – a major dearth in the field • Validation with GEO Ag CoP • Continue comparison with observational capabilities • Acquisition plans need to be flexible to keep pace with agricultural land use change

  25. Conclusions

  26. Acknowledgements • NASA Applied Science Program • NASA Earth and Space Science Fellowship Program • GEOGLAM Partners • Jeremy Mirmelstein • Louis Giglio • Luigi Boschetti • CEOS SEO – Brian Killough

More Related