The FGGD severe environmental constraints map is a global raster datalayer with a resolution of 5 arc-minutes. Pixels with no severe environmental constraints contain a value of zero. Each other pixel contains a cumulative class value that shows which environmental constraint is binding in the pixel area. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

WRIA_DEM: Hydrologically filled GTopo30 DEM with the main stems of cartographic rivers "burned-in" for irrigation analysis. GT30/GTopo30 is Global Topographic 30 arc second DEM database, nominal 1km postings; DEM is Digital Elevation Model. The WRIALAEA grid data layer is comprised of 9194x8736 derivative raster hydrologically filled dem features derived based on 1 kilometer data originally from FAO.

Derived from the Global Agro-Ecological Zones Study, Food and Agriculture Organization of the United Nations (FAO), Land and Water Development Division (AGL) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), 2000. Two sources of geo-referenced terrain slopes were available for use in the Global AEZ assessment: (i) terrain slopes indicated in the mapping unit expansion tables of the respective soil maps, and (ii) terrain slopes derived from GTOPO30 data (EROS Data Center, 1998). The latter terrain-slope database was established at IIASA using a rule-based algorithm to calculate slope distributions in terms of seven slope classes per 5 minute grid-cell of the DSMW soil data based on neighborhood relationships among grid-cells in the 30 arc-second GTOPO30 database. Slopes derived from the 30 arc-second DEM were allocated to soil units occurring within individual soil associations. This involved five steps: (i) Determination of slope classes for each 30 arc-second grid-cell of GTOPO30. Results are grouped in the following seven classes: 0-2%, 2-5%, 5-8%, 8-16%, 16-30%, 30-45% and > 45%; (ii) Aggregation of the results respectively to 5 minute latitude/longitude DSMW grid-cells, and to individual soil association map units resulting in a slope class distribution for each grid-cell and map unit; (iii) Defining priority classes of soil unit/slope relationships; (iv) Establishing for each soil association consistent rankings of slopes/soil units; (v) Allocation of individual soil units within a particular soil association map unit to 5 min grid-cells of the DSMW, according to calculated slope distributions.

Silt content (2-50/63 micro meter) mass fraction in ‰ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 5000 m cell.

The FGGD CV of LGP map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains an average coefficient of variation of LGP for the pixel area over the period 1901-1996. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

Derived from the Global Agro-Ecological Zones Study, Food and Agriculture Organization of the United Nations (FAO), Land and Water Development Division (AGL) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), 2000. Data averaged over a period of 37 years. Raster data-set has been exported as ASCII raster file type.

Grid with average Wet Day Frequency (rain days per month) for the period 1961-1990. This dataset is constructed from observations, backed with synthetic data derived from precipitation. Source: New, M., Lister, D., Hulme, M. and Makin, I., 2002: A high-resolution data set of surface climate over global land areas. Climate Research 21:1-25

The Food and Agriculture Organization of the United Nations (FAO) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), has developed a system that enables rational land-use planning on the basis of an inventory of land resources and evaluation of biophysical limitations and potentials. This is referred to as the Agro-ecological Zones (AEZ) methodology.