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Explore NASA and USDA partnership for timely global assessment of vegetation state and crop condition. Learn about satellite assets used for monitoring and transition process from research to operations.
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Global to Regional Agricultural Monitoring using Satellite DataNASA/GSFC – USDA/FAS Partnership Assaf Anyamba GEST/UMBC @GSFC – Biospheric Science Branch Weather and Agricultural Competitiveness Focus Area Session NASA/USDA Interagency Workshop Denver, Co. March 4-5, 2003
USDA/NASA Context • Global agricultural production effects US Agricultural competitiveness • Information required for both “domestic” production and “global” production from “competitor” countries in order to enhance the competitiveness of the US farmer in the global agriculture market place • Requirement for timely global assessment of vegetation state/crop condition in support of: • FAS • NASA/FAS LACIE>AGRISTARS>2000 MOU • Major Agricultural Regions during the growing season • Data combined with other information sources (weather, attaché, field reports, wire reports) • Estimates of Crop Production at the end if the growing season • USAID Famine Early Warning System (FEWS) • NASA/USAID and UN/FAO GIEWS Collaboration started in mid 80’s • Monitoring Drought susceptible areas, growing season • Drought indices developed based on multiple data sources – weather, satellite rainfall, water satisfaction, field and nutrition reports • Current Approach • Multi-year time series analysis using VI’s to determine deviations from ‘normal’ conditions (AVHRR, SPOT VEGETATION) • High resolution satellite data acquired “interest” with extreme anomalies (Landsat, Spot HRV, Ikonos) • High degree of analyst interpretation
Satellite Assets for Global Regional Agricultural Monitoring • Currently Used • Moderate Resolution • AVHRR, SPOT Vegetation (8km>1km) • MODIS AM/PM (Terra and Aqua) ( 1km>250m) • High Resolution • Landsat (30m >15m) • Hyperspatial Resolution • Ikonos (3m- - 1m) • Areas for Future Satellite Research • Hyperspectral Imaging for crop discrimination • Thermal imaging for crop stress monitoring
Technology / Science Transition Process (Research to Operations) Science Research and Development Operational Research and Development Operations Use (Enhancements) USDA/USAID/FEWS etc Time Transfer of technology in stages as the Research Develops – Ongoing Process
Issues Requiring Consideration • Time series analysis requires good inter calibration between instruments and sensors (NOAA-7 > NOAA14): leverage off NASA research on long term data sets for GCR • Timeliness of data delivery critical, redundancy in data provision desirable i.e. multiple data sources, AVHRR, SPOT Veg. etc • Relationship between products from different sources needs establishing • Just because new and better data exists doesn’t mean it is necessarily used - care is needed with technology insertion into the operational chain – e.g. period of overlap desirable, non-intrusive training process needed • Operators require high order products rather than raw data • Emphasis given to operational systems and data provision
FAS Agricultural Regions HERITAGE SYSTEM GSFC/GIMMS: • Provide Vegetation Index time series products from NOAA-AVHRR (8km) over FAS global agricultural regions thus release FAS from data production efforts to focus primarily on agricultural monitoring work. • Provide RD (new products, methods) for satellite vegetation products of that may be used by FAS • Serve as “backup” depository for FAS NOAA-AVHRR long-time series data sets. • Acquire from SPOT Image and archive on behalf of FAS, SPOT Vegetation 1-km NDVI and associated channel data, unpack, post-process, subset for use by FAS • Provide “on-demand” vegetation index products to FAS in case of emergencies (f.e. during Afghanistan crisis) • Provide satellite altimeter data for monitoring levels of large water bodies (lakes, reservoirs) important in irrigated agriculture especially in Middle East and Africa
NOAA/AVHRR 8km Products • All AVHRR products provided by continent • Long-term Mean NDVI surfaces (historical average) • 15 day NDVI composites • Monthly NDVI composites • Longterm Means (15-day &Monthly) • Longterm Maximum (15-day &Monthly) • Longterm Minimum (15-day &Monthly) • NDVI anomalies (15-day &Monthly) • Quality Flags ( Clouds & bad data: 15-day &Monthly) • JPG graphics of all products (Read for use)
NOAA/AVHRR 8km Products: Examples • Australia: Long-term Mean (1982-1999) NASA/GSFC-GIMMS Group
Examples NOAA/AVHRR 8km NDVI Products: • Long-term Minimum: February • Long-term Maximum: February NASA/GSFC-GIMMS Group • Long-term Mean: February
NOAA/AVHRR 8km NDVI Products: Examples • Cloud Frequency: February • NDVI Anomaly : February 1998 • Monthly NDVI: February 1998 The products provide “base line” metrics for agricultural monitoring NASA/GSFC-GIMMS Group
Crop Explorer = Automated Weather, Crop Models, & Vegetation Analysis Over Major Crop Regions Weather Data Crop Models Vegetation Indices • GAC (8-km) and LAC (1-km) from AVHRR-NOAA • SPOT-VEG (1-km)
TERRA/AQUAMODIS AVHRR/NOAA SPOT-VEG CADRE DBMS Images & time-series graphs generated at 8-km, 1-km, & 250-m resolutions Data Processed by NASA/GIMMS PCIWORKS(Image analysis) RASTERDBMS Required Automated products on web Interactivedata extraction Crop Explorerhttp://151.121.3.218/(Maps & time-series graphs over major crop regions) ArcGIS(Images, shape files, & graphs) ARCVIEW/CADRE (Multi-year comparisons) Data Flow for Current Project GAC (8-km) (1-km) (250-m) CADRE Grid Cells (40-km) GAC images (8-km) AUTOMATED 40-km grid cells INTERACTIVE
ACTIVITY: The Application of NASA EOS MODIS Data to Agricultural Assessment and Forecasting by the USDA Foreign Agricultural Service • Delivery and integration of Rapid Response data into the FAS monitoring system to facilitate improved monitoring of climate hazards, such as drought, large scale flooding, and snow storms, on agricultural production. • Development and testing of new MODIS RR products including new band combination products, a snow cover product, a MODIS continuity vegetation index and an enhanced vegetation index (EVI). • Establishing the relationship between MODIS VI data and the long-term archives from the AVHRR and SPOT-VEGETATION currently being used by PECAD. • Development of a distributed data and information system utilizing Internet GIS technology. RR products will be hosted by University of Maryland and made available to FAS personnel and eventually for public use. The interfaces will provide mosaicking, reprojection capabilities and common access to the deep archive of MODIS data prepared for the FAS at University of Maryland.
Colorado River DeltaVegetation Spatial and Temporal Dynamics with MODIS NDVI 2000-2001 Spring Summer June 9 June 25 May 25 Apr 7 July 11 Aug 12 Mar 22 Mar 6 Aug 28 Feb 18 Sept 13 Feb 2 Sept 29 Jan 17 Oct 15 Oct 31 Jan 1 Nov 16 Dec 18 Dec 2 Winter Fall NDVI TBRS, University of Arizona SCF Group, http://tbrs.arizona.edu A. Huete, Univ. of Arizona water 0.2 0.4 0.6 0.8 1.0
MODIS Rapid Response Project: Design Terra & Aqua USDA Forest Service Remote Sensing Application Center Direct Broadcast Receiving Station EDOS NOAA University of Maryland Geography Dept Rapid Response System NASA/GSFC GES DAAC NASA/GSFC L1B Data T+30min Cumulative Fire Maps http://www.fs.fed.us/eng/rsac Backup Feed L1B Data Twice Daily 5am/pm MST Active Fire Locations Burn Severity Maps Handcrafted Imagery T+5hrs Active Fire Locations Selected Imagery Active Fire Locations GOFC Fire Partners MODIS L0 Data T+2-5hrs T+5hrs Active Fire and Corrected Reflectance http://rapidfire.sci.gsfc.nasa.gov NASA Earth Observatory http://earthobservatory.nasa.gov MODIS home page http://modis.gsfc.nasa.gov Web Fire Maps and Fire Feature Server http://rapidresponse.umd.edu
Example of 250m Corrected Reflectance ProductBrazil/Bolivia (08/02/01) http://rapidfire.sci.gsfc.nasa.gov
Example of 250m Vegetation IndexRondonia, Brazil (08/02/01) http://rapidfire.sci.gsfc.nasa.gov
250m Growing Season (09/05/02) http://rapidfire.sci.gsfc.nasa.gov
250m After Harvest (10/05/02) http://rapidfire.sci.gsfc.nasa.gov
Nile Agricultural Region http://rapidfire.sci.gsfc.nasa.gov 250m I km
East Coast Snow Storm, Feb 1 km http://rapidfire.sci.gsfc.nasa.gov 250 m
500m http://rapidfire.sci.gsfc.nasa.gov 1km
IRAQ 1Km NCC (01/13/03) http://rapidfire.sci.gsfc.nasa.gov
IRAQ 250m NCC (01/13/03) http://rapidfire.sci.gsfc.nasa.gov
IRAQ 1km FCC (01/13/03) http://rapidfire.sci.gsfc.nasa.gov
IRAQ 250m FCC (01/13/03) http://rapidfire.sci.gsfc.nasa.gov
Next Steps – Short Term Strategy • Proceed with MODIS technology insertion with FAS – build on NASA MODIS research • Evaluation of New Indices and Products (EVI, LAI, LST) • Develop multi-source satellite data base for FAS (AVHRR, SPOT VEG, MODIS) • Closer link between NASA/USDA ag. field based research and operational users
Seasonal Patterns of Major Biomesin North America A. Huete, Univ. of Arizona
Next Steps – Long Term Strategy • Need to secure long term observations AVHRR>MODIS>VIIRS NPP > VIIRS NPOESS • NASA can help USDA make the case for VIIRS requirements • Need to ensure USDA requirements are included in the planning for data products and delivery from VIIRS • Need to explore improved crop production forecasting combining satellite and weather data (seasonal to interannual forecasts, El Nino/ La Nina Conditions etc: NSIPP, IRI) • Develop long term partnership between agencies e.g. joint projects and research announcements
WindSat/Coriolis EOS-Terra NPP EOS-Aqua Satellite Transition Schedule(9 March 2001)Slopes indicate 10-90% need (NPOESS GAP 5b) Projected End of Life based on 50% Need CY 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 0530 F18 F20 F16 C3 NPOESS DMSP 0730 - 1030 F17 F15 F19 C1 or C2 NPOESS NPOESS DMSP M POES METOP Local Equatorial Crossing Time 1330 N’ N L (16) C2 or C1 NPOESS POES Earliest Need to back-up launch S/C Deliveries Earliest Availability
El Nino / La Nino Impacts on Agriculture NASA/GSFC-NSIPP Forecast
NASA/GSFC-NSIPP Forecast A. Anyamba NASA/GSFC-GIMMS Group
NASA/GSFC-NSIPP Forecast A. Anyamba NASA/GSFC-GIMMS Group
NSIPP/IRI Forecast >> Vegetation Response >> Ag Production Estimates ?? NASA/GSFC-NSIPP Forecast A. Anyamba NASA/GSFC-GIMMS Group