1. Global NDVI Data for Climate Studies Compton Tucker NASA/Goddard Space Fight Center Greenbelt, Maryland 20771

2. NOAA AVHRR NDVI datasets NDVI is Normalized Difference Vegetation Index NDVI = (NIR – VIS) / (NIR + VIS) Global 8km data available daily since July 1981 Composites created at 15 day time step to create 27+ years of vegetation images with minimal clouds and artifacts. Drawbacks of AVHRR NDVI –Six (soon seven) different satellites used in series –Satellite orbit degrades over time, impacting the sun- sensor-view angle and thus the reflectances and NDVI Models cannot be used to fix problems because of complexity of surface and number of physical parameters.

3. NOAA Advanced Very High Resolution Radiometer NDVI Data Set Comparison 1.GSFC/DAAC PAthfinder Land (‘81-2000) 2.NOAA’s GVI data set(1981-2009…) 3.GIMMS precursor data sets (several) 4.GIMMS latest data set1981-2009… Same input data, different atmospheric corrections, different calibrations, different post processing normalization(s)

4. NDVI Data Sources AVHRR instruments (1981 – 2012 at least) MODIS instruments (2000 – 2009) SPOT Vegetation (1998 – 2009) SeaWiFS (1997 - 2009) Data Set considerations Must be quantitatively inter-comparable among sensors Must be non stationary Must be largely free of artifacts

5. NDVI Data Sets Direct linear relationship to FPAR Thus direct relationship to photosynthetic potential or capacity No a priori knowledge of surface required (i.e., vegetation type, etc.) Easily inter-calibrated among different remote sensing instruments (unlike EVI) Almost 28-year global record

6. NOAA-16 1982-20021992-2002 Decadal trends in terrestrial vegetation

7. NOAA AVHRR Channels 1 & 2 Ch 1 Ch 2 (Very broad or wide spectral bands) The NOAA person(s) responsible for these excellent examples of poor spectral resolution should be tarred and feathered.

8. Leaf Reflectance & Absorption Bean leaf x 3900

9. AVHRR NDVI analyses require Solar Zenith Angle correction

10. Use of Empirical Mode Decomposition to correct NDVI Empirical Mode Decomposition can identify and separate the real vegetative signal from artifacts. Because the Empirical Mode Decomposition derives functions from the data and is adaptive, it is perfectly suited to identify the NDVI trends associated with the solar zenith angles, and to leave the vegetation dynamics intact.

11. Solar Zenith Angle Variations by Latitude

12. Empirical Mode Decomposition processing for solar zenith angle errors

13. EMD solar zenith angle correction Range w/o SZA Correction: 0.12 ndvi units Range w/ SZA correction: 0.05 ndvi units Empirical Mode Decomposition/reconstruction (EMD) technique Requires no land cover information a priori

14. Regions affected by solar zenith angle drift in AVHRR record

15. Stratospheric Aerosol correction also required NOAA AVHRR 8-km NDVI Data Set Mt. Pinatubo, Philippines June 1991 Max. NDVI Effect 0.1-0.15 1991 corrected

16. Stratospheric Aerosol correction also required NOAA AVHRR 8-km NDVI Data Set El Chichon Mt. Pinatubo

17. Space Shuttle Limb Photographs Before Mt. Pinatubo Eruption After Mt. Pinatubo Eruption

18. NOAA AVHRR 8-km NDVI Data Set El Chichon (1982-1984)Mt. Pinatubo (1991-1994)

19. NOAA AVHRR 8-km NDVI Data Set Diffuse average daily PAR[W/m2/mic] (0.4-0.7 mic) El Chichon (1982-1984)Mt. Pinatubo (1991-1994)

20. NDVI Data 1981 – 2007