Global Inventory Modeling and Mapping Studies (GIMMS)

Data Access
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The GIMMS (Global Inventory Modeling and Mapping Studies) data set is a normalized difference vegetation index (NDVI) product available for a 25 year period spanning from 1981 to 2006. The data set is derived from imagery obtained from the Advanced Very High Resolution Radiometer (AVHRR) instrument onboard the NOAA satellite series 7, 9, 11, 14, 16 and 17. This is an NDVI dataset that has been corrected for calibration, view geometry, volcanic aerosols, and other effects not related to vegetation change.

Code Values
Value Label
0.0 - 1.0 NDVI
-0.1 Water
-0.05 Null
How to Cite This Data Set

Citation Format: Author (Publication Date), Collection Name, Product Name, Version, Collection Publisher, Publisher Location, Product Coverage Date.

Citation Parameters Example:

  • Author: Tucker, C.J., J.E. Pinzon, M.E. Brown
  • Publication Date: 2004
  • Collection Name: Global Inventory Modeling and Mapping Studies
  • Product Name: (specify image name from metadata or naming convention)
  • Processing Level: 2.0
  • Publisher: Global Land Cover Facility, University of Maryland
  • Publisher Location: College Park, Maryland
  • Product Coverage Date: {specify from metadata or naming convention}

Full Example Citation: Tucker, C.J., J.E. Pinzon, and M.E. Brown (2004), Global Inventory Modeling and Mapping Studies, NA94apr15b.n11-VIg, 2.0, Global Land Cover Facility, University of Maryland, College Park, Maryland, 04/15/1994.

Associated Peer-Reviewed Publication (cite these publications whenever the data are used):
Pinzon, J., Brown, M.E. and Tucker, C.J., 2005. Satellite time series correction of orbital drift artifacts using empirical mode decomposition. In: N. Huang (Editor), Hilbert-Huang Transform: Introduction and Applications, pp. 167-186.

Tucker, C.J., J. E. Pinzon, M. E. Brown, D. Slayback, E. W. Pak, R. Mahoney, E. Vermote and N. El Saleous (2005), An Extended AVHRR 8-km NDVI Data Set Compatible with MODIS and SPOT Vegetation NDVI Data. International Journal of Remote Sensing, Vol 26:20, pp 4485-5598.

Intellectual Property Rights

University of Maryland; Department of Geography; use is free to all if acknowledgement is made. UMD holds ultimate copyright.


Source for this data set is the Global Land Cover Facility,

Copyright © 1997-2014 University of Maryland. All rights reserved
University of Maryland National Aeronautics and Space Administration GOFC_GOLD