The raster dataset consists of a 500m score grid for the cassava 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 )

The raster dataset consists of a 500m score grid for rice 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” *0.1 ) + (”Railway Stations Accessibility” *0.1 ) + (”Poverty” *0.1 )

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)

The raster dataset consists of a 1000 m score grid for crops 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: Cassava. • 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" * 0.35) + (“Railway Accessibility” * 0.25) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1)

The raster dataset consists of a 500m score grid for millet 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” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1)

The raster dataset consists of a 500 m score grid for the crop 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: Fruits. • 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) + (“Major Cities Accessibility” * 0.1) + (”Poverty” * 0.1) + ("Human Population Density" * 0.2) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.1).

Data publication: 2022-04-11

Contact points:

Resource Contact: FAO-Data

Resource Contact: Dariia Nesterenko

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:

1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. https://data.apps.fao.org/catalog/iso/304c21fb-0f5a-44ad-9948-2af6a7144fb5
2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. https://data.apps.fao.org/map/catalog/srv/eng/catalog.search;jsessionid=4AA4D377D0F90E3328ACBDB5C21BFFC6?node=srv#/metadata/0c6be5d1-3a73-4516-953b-dbe2b511d6b3
3. OpenStreetMap.
4. Poverty – Atlas AI 2020. https://docs.atlasai.co/economic%20well-being/asset_wealth/

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Zipped TIF raster file for Crop Storage Location Score: Fruits (Gabon - ~ 500 m)

The raster dataset consists of a 500m score grid for dairy processing industry facilities siting, 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 and sheep dairy production intensification potential defined using crop production, livestock production systems, and goat and sheep distribution.

The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, goat and sheep distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) 4. Poverty.

It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.3) + ("Human Population Density" * 0.1) + (“Major Cities Accessibility” * 0.1) + ( "Poverty" * 0.1) + (”dairyIntensification” * 0.4).

Data publication: 2021-10-18

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Dariia Nesterenko

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets: 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. 3. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2) 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap. 6. Poverty rates.

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Dairy Processing Location Score: Goat and Sheep (Tajikistan- ~ 500m)

The raster dataset consists of a 500m score grid for dairy processing industry (UHT and milk powder) facilities siting, 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 cattle dairy production intensification potential, defined using crop production, livestock production systems and cattle distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, cattle distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) 4. Poverty. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.3) + ("Human Population Density" * 0.1) + (“Major Cities Accessibility” * 0.1) + ( "Poverty" * 0.1)+(”dairyIntensification” * 0.4)

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).

Data publication: 2020-08-03

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Nelson Ribeiro

Data lineage:

Two major sources were used, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:

1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km.

2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units: • Production (mt); crops - bean, cowp;

3. OpenStreetMap - road, railways and places layers.

4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports;

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

The raster dataset consists of a 500 m score grid for fruits 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: Coffee. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.2) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.1)

The raster dataset consists of a 1km score grid for sweet potato 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).

The raster dataset consists of a 500 m score grid for fruits 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: Fruits. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2)

The raster dataset consists of a 500m score grid for tropical fruits 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” *0.1 ) + (”Railway Stations Accessibility” *0.1 ) + (”Poverty” *0.1 )

The raster dataset consists of a 500 m score grid for fruits 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: Vegetables. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2)

The raster dataset consists of a 500m score grid for dairy processing industry facilities siting, 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 buffalo dairy production intensification potential defined using crop production, livestock production systems, and buffalo distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, buffalo distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) 4. Poverty. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.25) + ("Human Population Density" * 0.1) + (“Major Cities Accessibility” * 0.1) + (“ Accessibility to ports” * 0.1) + ( "Poverty" * 0.1) + (”Dairy Intensification” * 0.35).

The raster dataset consists of a 500m score grid for pulses 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” *0.1 ) + (”Railway Stations Accessibility” *0.1 ) + (”Poverty” *0.1 )

The raster dataset consists of a 500 m score grid for fruits 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: Vegetables. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.2) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.1)

The raster dataset consists of a 500m score grid for vegetables 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” *0.1 ) + (”Port Accessibility” *0. 2)

The raster dataset consists of a 500m score grid for the vegetable 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” *0.1 ) + (”Port Accessibility” *0.1 ) + (”Asset Wealth” *0.1 )

The raster dataset consists of a 500m score grid for cotton storage location achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse location: • Supply: Cotton. • 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) + (“Poverty” * 0.1) + ("Major Ports Accessibility" * 0.1)+("Major Regional Cities Accessibility" * 0.1). This 500m 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).