Global Assessment of Land Degradation and Improvement (GLADA)

GLADA is an attempt to follow up on the GLASOD study through a more detailed and more accurate global assessment of the status and trends of land degradation and the identification of hotspots suffering extreme constraints or at severe risk, as well as areas where degradation has been arrested or reversed. The approach involves the integration of simple indicators derived from time-series of remote sensing products (in particular MODIS), with climatic, land cover and terrain data . The remote sensing indicators are mainly proxies for the state and trend of biomass productivity, such as the annual Normalized Difference Vegetation Index (NDVI).  GLADA analyzes long-term trends in biomass productivity using the GIMMS dataset of corrected NDVI 1981-2003 with 5 arc-minute (9 km at the equator) spatial resolution. Rain-use-efficiency (RUE) is used to adjust NDVI trends and exclude biomass variations related to rainfall. The RUE-adjusted NDVI trends form the basis for deciding  which areas are degrading or improving. To ensure  changes in degradation status are not attributed to land use changes, a comparison is made between land use in the beginning of the time series and at the end using land use maps.

The GLADA methodology has been applied globally and has been tested in six pilot countries (Argentina, China, Cuba, Senegal, South Africa, and Tunisia).