Crop Storage Location Score: Potato (Kenya - ~ 1Km)

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). **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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. OpenStreetMap. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped TIF raster file for Kenya sweet potato storage/warehouse location score.

The raster dataset consists of a 1km score grid for cassava 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). **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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. OpenStreetMap. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped TIF raster file for Kenya cassava storage/warehouse location score.

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). **Data revision:** 2022-04-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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); 3. OpenStreetMap - Map of the world built by volunteers and released with open-content license. Community mapping using wiki-style collaborative editing software. The data was downloaded in ESRI SHP file format for the selected countries. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** download Kenya maize warehouse location score

The raster dataset consists of a 1km score grid for beans 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). **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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. OpenStreetMap. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped TIF raster file for Kenya beans storage/warehouse location score.

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). **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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); pota, swpo, cass; 3. OpenStreetMap - Road, railways and places layers; 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:**

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) **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement 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: sugc, maiz, pota, swpo, cass, bean, whea, sorg, cowp, rice, acof/rcof; 3. OpenStreetMap - Map of the world built by volunteers and released with open-content license. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:**