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Background

The weekly 0.144-degree resolution global vegetation index (GVI) from NOAA (National Oceanic and Atmospheric Administration) / NESDIS (National Environmental Satellites Data and Information Services) has a long history starting late 1981 and has included data derived from AVHRR (Advanced Very High Resolution Radiometer) sensors onboard NOAA-7, 9, 11, 14, 16, 17 and 18 satellites. Even after post-launch calibration and mathematical smoothing and filtering of the Normalized Difference Vegetation Index (NDVI) derived from AVHRR visible and near infrared channels, the time series of smoothed global NDVI still has apparent discontinuities and biases due to sensor degradation, orbital drift (equator crossing time), and differences from instrument to instrument in band response functions. To meet the needs of the operational weather and climate modeling and monitoring community for a stable long term global NDVI dataset, we investigated adjustments to substantially reduce the bias of the weekly global smoothed NDVI (SMN) series by simple and efficient algorithms that require a minimum number of assumptions about the statistical properties of the inter-annual global vegetation changes. Of the algorithms tested, we found the Adjusted Cumulative Distribution Function (ACDF) method to be a well balanced approach that effectively eliminated most of the long term global scale inter-annual trend of AVHRR NDVI. Improvements to the global and regional NDVI data stability have been demonstrated by the results of ACDF adjusted dataset evaluated at global scale, on major land classes, with relevance to satellite equator crossing time, at major continental regions, and for applications of regional drought detection.

The Experimental Global Vegetation Processing System (GVPS) takes the Second Generation Global Vegetation Index (GVI) weekly data of AVHRR channels 1, 2 and 4 as input and generates the global Vegetation Health Indices and Green Vegetation Fraction with a resolution of 0.144-degree.

The Green Vegetation Fraction (GVF) is critical in surface fluxes simulation for coupled land-atmospheric models.  The weekly real-time GVF product is an improvement over the currently used climatologically mean monthly GVF in NOAA/NCEP's operational Eta mode.

Additional Products from this system include NDVI, Brightness Temperature, smoothed NDVI, T, Vegetation Health Indices, and Green Vegetation Fraction (GVF), among which the smoothed NDVI is an improvement over the NDVI provided in the previous GVI system.

The Vegetation Health Indices are used for drought monitoring which include Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation-Temperature Index (VTI, also called Vegetation Health Index).