Dec 15, 2004 AGUMolly E. Brown, PhD1 Inter-Sensor Validation of NDVI time series from AVHRR, SPOT-Vegetation, SeaWIFS, MODIS, and LandSAT ETM+ Molly E. Brown + Jorge E. Pinzon + Jeffery T. Morisette x Kamel Didan* Compton J. Tucker x + SSAI, NASA Goddard Space Flight Center * Soil, Water and Environmental Sciences Greenbelt, MD University of Arizona x NASA Goddard Space Flight Center Greenbelt, MD 20771

Dec 15, 2004 AGUMolly E. Brown, PhD2 Overview Data used in study –Global NDVI datasets, LandSAT ETM+ for comparison Methods –Spectral, spatial and temporal considerations –Global 1 degree datasets –CEOS sites and drought locations Results Discussion – data continuity from AVHRR through MODIS to VIIRS

Dec 15, 2004 AGUMolly E. Brown, PhD3 VIS/NIR/SWIR Band Comparison AVHRR SeaWiFS VGT MODIS Differences in spectral range will necessitate increased processing in AVHRR and SPOT due to water vapor sensitivity.

Dec 15, 2004 AGUMolly E. Brown, PhD4 Data SensorData SourceSpatial Resolution Time domain Temporal Resolution AVHRR GIMMS NDVIg Pinzon et al (2005) 8000 m 1 degree mon 15 day monthly SPOT VGT FAS-GIMMS, VITO Achard, F. et al. (1992) 1000 m 1 degree mon 10 day monthly MODIS NDVI MODIS-Land, University of Arizona (K.Didan) Huete, A. et al. (2002) ~5000 m, 500m 1 degree mon 16 day monthly SeaWIFS SeaWIFS / GSFC / GIMMS Tucker et al (2002) 4633 m 1 degree mon monthly LandSAT CEOS website Morisette et al (2004) 30 m1-9 scenes periodic

Dec 15, 2004 AGUMolly E. Brown, PhD5 Validation Methods: 59 Sites Aggregations to monthly time step and 1 degree resolution for pixel by pixel comparison. Global hemispherical means created to provide direct comparison of NDVI behavior. Comparisons of time series created from 25x25 km box at native temporal and spatial resolutions: CEOS sites, locations of droughts, deserts, agricultural production regions, etc. Anomaly and seasonal characteristics evaluated Atmospherically corrected, 25x25km subsets of selected LandSAT ETM+ scenes provide a base for comparison of datasets. CEOS Land Validation Sites

Dec 15, 2004 AGUMolly E. Brown, PhD6 Maps of NDVI correlation at 1degree

Dec 15, 2004 AGUMolly E. Brown, PhD7 Global averages show that Four sensors have similar signals. Improvements in AVHRR NDVI have reduced many differences between the sensors, enabling a direct comparison between the records: Longer base means for anomaly Multiple data sources for NDVI More work to be done for data integration to be operational

Dec 15, 2004 AGUMolly E. Brown, PhD8 Note: similarity in range, seasonality of NDVI LandSAT scene range of variation Differences in treatment of winter, clouds Correlations: AV-SP 0.89 AV-MO 0.84 AV-SW 0.86 Results from CEOS Sites: Harvard, Massachusetts

Dec 15, 2004 AGUMolly E. Brown, PhD9 Correlations: AV-SP 0.59 AV-MO 0.65 AV-SW 0.59 Correlations: AV-SP 0.85 AV-MO 0.82 AV-SW 0.66

Dec 15, 2004 AGUMolly E. Brown, PhD10 MODIS cloud and aerosol atmospheric correction explains the differences between MODIS and the other sensors. Correlations AV-SP 0.60 AV-MO 0.33 AV-SW

Dec 15, 2004 AGUMolly E. Brown, PhD11 Anomaly Time Series: Drought Detection

Dec 15, 2004 AGUMolly E. Brown, PhD12 Conclusions Many lessons have been learned from the creation of a consistent NDVI record from AVHRR –How to integrate sensors with different gains (NOAA 7-14 and NOAA 16-17) –Overcome sensor limitations to reduce clouds, reduce noise and improve image coherence More work to be done on further integrating the records of AVHRR, MODIS, SPOT, SeaWIFS to maximize their various strengths, minimizing their weaknesses AVHRR – MODIS – VIIRS data continuity will be required to maximize length of record to answer important science questions

Dec 15, 2004 AGUMolly E. Brown, PhD13 Thanks go to Brad Doorn, Assaf Anyamba and Jennifer Small for providing the SPOT data, Gene Feldman, Norman Kuring and Jacques Descloitres for the monthly global SeaWIFS data. URLs: –GIMMS NDVIg: –SeaWIFS: –MODIS: –SPOT VGT: –Subsets of SPOT, AVHRR, MODIS tiles, and Landsat ETM+ data at CEOS sites: Thank you!