Moisture regime classification at about 9 km resolution at the equator, using different climate data source and based on different Representative Concentration Pathways (RCPs) according to the time period as follows: - climate data source CRUTS32 based on historical data for the time period 1981-2010; - climate data source ENSEMBLE based on the Representative Concentration Pathway RCP8.5 for time periods 2041-2070 and 2071-2100. The Moisture regime classification dataset is part of the GAEZ v4 Theme 1 Land and Water Resources, Agro-Ecological Zones sub-theme. The agro-ecological zones classification provides a characterization of bio-physical resources relevant to agricultural production systems. AEZ definitions and map classes follow a rigorous methodology and an explicit set of principles. The inventory combines spatial layers of thermal and moisture regimes with broad categories of soil/terrain qualities. It also indicates locations of areas with irrigated soils and shows land with severely limiting bio-physical constraints including very cold and very dry (desert) areas as well as areas with very steep terrain or very poor soil/terrain conditions. For further details, please refer to the GAEZ v4 Model Documentation.

Theme 4 presents results of the final step in the GAEZ crop suitability and productivity assessment, combining agro-climatic potential yields with soil/terrain evaluation results, i.e., yield reduction factors due to the constraints induced by soil limitations and prevailing terrain-slope conditions. Grid cells of the resource inventory can be made up of multiple soil types and terrain slope classes. GAEZ determines for each grid cell the respective characteristics of land units in terms of soil types and slope classes. Each of these component land units is separately assessed and assigned a suitability rating and simulated potential yield. The values are accumulated over all component land units in a grid cell, which produces a distribution of results falling into different suitability classes: very suitable (VS), suitable (S), moderately suitable (MS), marginally suitable (mS), very marginally suitable (vmS) and not suitable (NS). This theme provides information for 53 crops and includes sub-themes on: (1) Suitability Class, (2) Suitability Index, (3) Agro-ecological Attainable Yield, and (4) Crop Water Indicators. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Classification by thermal climates and thermal zones dataset at about 9 km resolution at the equator. CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Classification by thermal climates and thermal zones dataset is part of the GAEZ v4 Theme 2 Agro-climatic Resources - Climate Classification sub-theme. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.

The Koeppen-Geiger climate classification is based on a subdivision of terrestrial climates into five major types, which are represented by the capital letters A (tropical), B (dry), C (temperate), D (cold), and E (polar). Each of these climate types, except for B, is defined by temperature criteria. Type B designates climates in which the controlling factor on vegetation is dryness (rather than coldness). Dry climates are divided into arid (BW) and semi-arid (BS) subtypes. Other climate types are sub-divided according to seasonal precipitation characteristics. The level-2 classification distinguishes 14 classes. CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Koeppen-Geiger climate classification dataset is part of the GAEZ v4 Theme 2 Agro-climatic Resources, Climate Classification sub-theme. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.

The Thermal zones dataset, at about 9 km resolution, reflects actual monthly temperature conditions throughout the year and serve as input to crop suitability assessment. CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Thermal zones dataset is part of the GAEZ v4 Theme 2 Agro-climatic Resources, Climate Classification sub-theme. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.

The quality and availability of land and water resources, together with socio-economic conditions and institutional factors, are essential to assure sustainable food security. GAEZ provides a framework for establishing a spatial inventory of land resources. Global environmental datasets provide the spatial characteristics required for land productivity assessments concerning location-specific agro-ecological conditions. The land resources inventory contains spatial layers of climate, land cover, soil, elevation and terrain slopes, protected areas and areas of high biodiversity value, administrative units, watersheds, population and livestock distribution. Theme 1: Land and Water Resources provides selected layers of the GAEZ v4 land resources database organized in several sub-themes of (1) Agro-ecological Zones, (2) Land Cover, (3) Soil Resources, (4) Soil Suitability, (5) Terrain Resources, (6) Exclusion Areas, (7) Water Resources, and (8) Selected Socio-economic Data. Results of this theme are presented in a regular raster format of 5 arc-minute (about 9 x 9 km at the equator) grid cells. Selected maps related to AEZ classification, soil suitability, terrain slopes and land cover are provided at 30 arc-second (0.9 x 0.9 km) resolution. The GAEZ v4 update includes 2010 baseline data comprising land cover, a harmonized global soil database and terrain data, protected areas and areas of high biodiversity value. Climatic conditions are based on a time series of historical data of 1961-2010 and a selection of future climate simulations (30-year average of years 2011-2040, 2041-2070, and 2070-2099) using recent IPCC AR5 Earth System Model (ESM) outputs for four Representative Concentration Pathways (RCPs). GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Agricultural production and land statistics are available at national scale from FAOSTAT database, but these statistical data cannot capture the spatial heterogeneity of agricultural production systems at fine resolutions within country boundaries. In this case a “downscaling” method is needed for plausible attribution of aggregate national production statistics to individual spatial units (grid cells) by applying formal methods that account for land characteristics, assess possible production options and can use available evidence from observed or inferred geo-spatial information, including remotely sensed land cover, soil, climate and vegetation distribution, population density and distribution, etc. Theme 5 spatial layers include mapped distributions of harvested area, yield and production at 5 arc-minute resolution for 26 major crops/crop groups, separately in rain-fed and irrigated cropland. Country totals are based on FAO statistics for the years 2009-2011. Also included are estimates of the spatial distribution of total crop production value and the production values of major crop groups (cereals, root crops, oil crops), all valued at year 2000 international prices, separately for rain-fed and irrigated cropland. This theme is organized into two main sub-themes: (1) Area, Yield and Production, and (2) Aggregate Crop Production Value. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Yield gaps provide important information for identifying causes of food insecurity and addressing rural poverty. Yield and production gaps have been estimated by comparing at a spatially detailed level of 5 arc-minutes the agro-ecological attainable yield and production of 22 major crops/crop groups (see Theme 4), simulated under the historical climate of 1981-2010, with actual yields and production obtained by downscaling for the years 2000 and 2010 statistical data of main food, feed and fiber crops (see Theme 5). Comparisons are done separately for rain-fed and irrigated cropland and are presented as crop yield achievement ratios for yields, computed as actual over potential yield, and as absolute values for the difference of potential and actual production. Theme 6 provides information about: (1) Crop Yield Achievement Ratio, (2) Production Gap, and (3) Aggregate Yield Achievement Ratio. Results of this theme are presented in a regular raster format of 5 arc-minute (about 9 x 9 km at the equator) grid cells. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Crop cultivation potential describes the agronomically possible upper limit to produce individual crops under given agro-climatic, soil and terrain conditions and applying specific management assumptions and agronomic input levels. Soil moisture conditions together with other climate characteristics (radiation and temperature) during different crop development stages are used in an eco-physiological crop growth model to calculate potential biomass production and yield. The constraint-free crop yields calculated in the AEZ biomass model reflect yield potentials with regard to temperature and radiation regimes prevailing in each grid-cell. Maximum biomass and yields depend on the timing of the crop growth cycle (crop calendar) and are separately calculated for irrigated and rain-fed conditions. Crop specific requirements are matched with temperature regimes prevailing in individual grid-cells. Matching is tested for the full range of possible starting dates. For rain-fed conditions the crop calendar resulting in the highest expected (water-limited) yield is selected to represent maximum biomass and agro-climatic potential yield of the respective crop in a particular grid-cell. The estimation of yield losses due to water stress is based on crop-specific water balances. Yield estimation for irrigation conditions assumes that irrigation is scheduled such that no yield-reducing crop water deficits occur during the crop growth cycle. Differences in crop types and production systems are empirically characterized by the concept of Land Utilization Types (LUTs). A LUT comprises technical specifications for crop production within a given socioeconomic setting. Specific LUT attributes include agronomic information, type of the main produce, water supply type, information on typical cultivation practices, and utilization of main produce. GAEZ v4 distinguishes more than 300 crops/LUTs per level of inputs/management, which are separately assessed for rain-fed and irrigated conditions. These LUTs are grouped into 67 crop sub-types and 53 different food, feed, fiber, and bio-energy crops. Theme 3 provides crop-wise information about: (1) Agro-Climatic Yield, (2) Constraint Factors, (3) Growth Cycle Attributes, and (4) Land Utilization Types (LUT) Selection. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

In GAEZ, the procedures proposed by Nelson and Outcalt (1987) are applied to calculate an air frost index (FI) which is used to characterize climate-derived permafrost conditions into four classes: (i) Continuous permafrost (ii) Discontinuous permafrost (iii) Sporadic permafrost (iv) No permafrost Reference permafrost zones are determined based on prevailing daily mean air temperature (Ta). The air frost index (FI) is calculated and used to characterize permafrost areas. For this calculation, accumulated degree-days, above and below 0oC, are used to calculate the thawing index (DDT) and the freezing index (DDF). CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Permafrost zones classification dataset is part of the GAEZ v4 Theme 2 Agro-Climatic Resources, Climate Classification sub-theme. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.