The raster dataset consists of a 1km score grid for Maize storage sites achieved by processing sub-model outputs that characterize logistical factors for crop warehouse location: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + (“Major Cities Weighted Accessibility” * 0.1) + (”Regional Cities Weighted Accessibility” * 0.1) This 1km resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

Country raster grid with 0.01 decimal degrees resolution produced under the scope of the sub-Saharan African Corridor project pilot case, using raster-based Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) methodology for the identification and definition of mobile storage locations (movable warehouses). The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are Cereal Crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). The main transportation network infrastructure is the input for the development of raster-based travel time/cost analysis. GIS multicriteria decision analysis GIS-MCDA consists of a method to convert and combine spatial data/geographical information and decision-makers criteria in order to attain evidence for a decision-making process. Considered cereal crops: maize, wheat, sorghum and rice. The location score results from an arithmetic weighted sum calculation (cell statistics) of normalized grids, generating a location score varying from 0 to 100. The assumed weight for each of the criteria is as follows. ("Cereal Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) + ("Ports Accessibility" * 0.1)

Country raster grid with 0.01 decimal degrees resolution produced under the scope of the sub-Saharan African Corridor project pilot case, using raster-based Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) methodology for the identification and definition of mobile storage locations (movable warehouses). The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are major crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). The main transportation network infrastructure is the input for the development of raster-based travel time/cost analysis. GIS multicriteria decision analysis GIS-MCDA consists of a method to convert and combine spatial data/geographical information and decision-makers criteria in order to attain evidence for a decision-making process. The location score results from a simple arithmetic weighted sum calculation (cell statistics) of normalized grids, generating a location score varying from 0 to 100. The assumed weight for each of the criteria is as follows. ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) + ("Ports Accessibility" * 0.1)

Crop Storage Location Score: Legume (Kenya - ~1km) is a country raster grid with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification of recommended mobile storage locations (movable warehouses). The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. The variables are Legume Crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). The main transportation network infrastructure is the input for the development of raster-based travel time/cost analysis. GIS multicriteria decision analysis GIS-MCDA consists of a method to convert and combine spatial data/geographical information and decision-makers criteria in order to attain evidence for a decision-making process. Considered crops are selected using FAOStat data: Beans, Cow Peas, dry. The location score (0-100) results from an arithmetic weighted sum calculation (cell statistics) of normalized grids. The assumed weight for each of the criteria is as follows. ("Legume Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) + ("Ports Accessibility" * 0.1)

Crop Storage Location Score: Root Crops (Kenya - ~1km) is a 0.01 degrees resolution country raster grid, produced under the scope of the sub-Saharan African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification of mobile storage recommended locations (movable warehouses). The modelling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are Root Crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). The main transportation network infrastructure is the input for the development of raster-based travel time/cost analysis. GIS multicriteria decision analysis GIS-MCDA consists of a method to convert and combine spatial data/geographical information and decision-makers criteria in order to attain evidence for a decision-making process. Considered crops are defined using FAOStat data: Potatoes, Sweet Potato, Cassava. The location score varying from 0 to 100 results from an arithmetic weighted sum calculation (cell statistics) of normalized grids. The assumed weight for each of the criteria is as follows. ("Root Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) + ("Ports Accessibility" * 0.1)

Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the largest cities (>50k habitants) in the country. This 1km resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

Raster grid covering the country with 0.01 decimal degrees resolution produced under the scope of the sub-Saharan African Corridor project pilot case, using raster-based Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) methodology for the identification and definition of mobile storage locations (movable warehouses). The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are major crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). The main transportation network infrastructure is the input for the development of a raster-based travel time/cost analysis. GIS multicriteria decision analysis GIS-MCDA consists of a method to convert and combine spatial data/geographical information and decision-makers criteria in order to attain evidence for a decision-making process. The location score is obtained by way of a simple arithmetic weighted sum calculation (raster calculator tool) of reclassified grids, generating a location score varying from 0 to 3. The assumed weight for each of the criteria is as follows. ("Crop Production" * 0.4) + ("Human Population Density" * 0.3) + ("Cumulative Travel Time/Cost" * 0.3)

The raster dataset consists of a 500 m score grid for slaughterhouse industry facilities, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on goat production intensification potential defined using crop production, livestock production systems, and goat density. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, dairy herd distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.2) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.3) + (”Goat Intensification” * 0.3)

The raster dataset consists of a 500m score grid for cotton storage location, 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 that characterize logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.2) + (”Asset Wealth” * 0.1)

Travel time/cost surface (raster grid), port accessibility map for Kenya's Mombasa port. Outputs produced in the sub-Saharan African Corridor, Mobile Warehouse Location pilot project. The calculation of cost/time distance surfaces is based on some assumptions: A. Road travel time/cost is computed for large trucks only, it is assumed that the accessibility is related to large cargo freight vehicles, tertiary and local traffic roads are not included; B. Lake and river navigation are treated as a surface (polygons) not taking into consideration navigation infrastructure (points). The steps to produce travel time surfaces are: rasterization of transportation network vector layers and surfaces, production of cost/time layer summing different grids cell values, and computation of a cumulative cost/time layer (Ports Accessibility Map).