Global trends in NDVI-derived parameters obtained from GIMMS data

The Normalized Difference Vegetation Index (NDVI) has been proven to be useful to assess vegetation changes around the world, in spite of limitations such as sensitivity to cloud or snow contamination. In order to map vegetation changes at global scale, this study uses NDVI time series provided by the GIMMS (Global Inventory Modeling and Mapping Studies) group, which were fitted annually to a double logistic function. This fitting procedure allowed for retrieval of NDVI-derived parameters which were tested for trends using Mann-Kendall statistics. These trends were validated by comparison at 73 ground control points documented as change hotspots. The obtained trends for NDVI-derived parameters provide information to the remote sensing community on the regions more susceptible to having suffered changes, to complement other traditional methods such as national inventories and field work. Additionally, the validation procedure can be applied to any results obtained from a global dataset.