The Gridded Livestock of the World (GLW) is a global livestock mapping project by the Food and Agriculture Organization's Animal Production and Health Division (FAO-AGA). It describes the global spatial distribution of cattle, buffaloes, sheep, goats, pigs and poultry. The most-detailed sub-national census data are disaggregated based on statistical relations with some environmental variables in similar agro-ecological zones.

Crop suitability index in classes, current cropland in grid cell for wheat, cotton and sugarcane under irrigated conditions and high input level, with and without CO2 fertilization, 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 period 2041-2070. The Crop suitability index in classes dataset is part of the GAEZ v4 Suitability and Attainable Yield - Suitability Class. For additional information, please refer to the GAEZ v4 Model Documentation.

Crop suitability index in classes, all land in grid cell for wheat, cotton and sugarcane under rain-fed conditions and high input level, with and without CO2 fertilization, 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 period 2041-2070. The Crop suitability index in classes dataset is part of the GAEZ v4 Theme 4 Suitability and Attainable Yield, Suitability Class sub-theme. For additional information, please refer to the GAEZ v4 Model Documentation.

Production for the year 2010 for wheat, cotton and sugarcane under rain-fed, irrigated and total water supply conditions. The Crop Production dataset, at about 5 km resolution, is part of the GAEZ v4 Actual Yields and Production - Area, Yield and Production sub-theme. For additional information, please refer to the GAEZ v4 Model Documentation.

The Multi-cropping classification dataset at about 9 km resolution represents a classification in terms of sequential multi-cropping zones under rain-fed conditions. CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Multi-cropping classification dataset is part of the GAEZ v4 Theme 2 Agro-climatic Resources, Climate Classification sub-theme. In the GAEZ crop suitability analysis, the LUTs considered refer to single cropping of sole crops, i.e., each crop is presumed to occupy the land only once a year and in pure stand. Consequently, in areas where the growing periods are sufficiently long to allow more than one crop to be grown in the same year or season, single crop yields of annual crops do not reflect the full potential of total time available each year for rain-fed or irrigated crop production. To assess the multiple cropping potential, a number of multiple cropping zones have been defined through matching both growth cycle and temperature requirements of individual suitable crops with time available for crop growth. For rain-fed conditions this period is approximated by the LGP, i.e., the number of days during which both temperature and moisture conditions permit crop growth. Under irrigation conditions the length of the temperature growing period and annual accumulated temperature sums are decisive. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.

The combination of yield gap and poverty rates into a single map enables to identify best feasible modalities for agricultural development, potential investment, and resource allocation. - Yield gap provides 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, 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. - The poverty map portrays poverty rates at the country level. Poverty rates vary from 12.7 to 76.2 percent. Accordingly, the higher percentage of poverty in a particular area, the poorer population is located there.

Temperature regimes, solar radiation and available soil moisture determine photosynthesis, which allows plants to accumulate dry matter throughout the plant development stages. Compilation of an AEZ agro-climatic inventory using several climatic variables (e.g. temperature, precipitation, sunshine fraction, relative humidity) gives a general characterization of climatic resources, signifies their suitability for agricultural use and provides data and indicators related to climatic requirements of crop growth, development and yield formation. The inventory includes a variety of agronomically relevant characteristics of prevailing thermal and moisture regimes, and growing periods. GAEZv4 climate data include historical (time-series and 30-year averages covering 1961-2010) and future periods (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). This theme 2 provides information about (1) Climate Classification, (2) Thermal Regime, (3) Moisture Regime and (4) Growing Period. 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. Climatic conditions are based on a time series of historical data of 1961-2010 and a selection of future climate simulations 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.

Output density (potential production divided by total grid cell area) for wheat, cotton and sugarcane under rain-fed conditions and high input level, with and without CO2 fertilization, 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 period 2041-2070. The Output density (potential production divided by total grid cell area) dataset is part of the GAEZ v4 Theme 4 Suitability and Attainable Yield, Agro-ecological Attainable Yield sub-theme. For additional information, please refer to the GAEZ v4 Model Documentation.

The combination of yield gap and poverty rates into a single map enables to identify best feasible modalities for agricultural development, potential investment, and resource allocation. - Yield gap provides 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, 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. - The poverty map portrays poverty rates at the country level. Accordingly, the higher percentage of poverty in a particular area, the poorer population is located there.

The 1km raster dataset represents top location score areas filtered by exclusive criteria: access to finance, distance to major roads and access to IT. The layer is produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20 km (0.18 degree) buffer radius. • Major roads - approx. 2 km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map.