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Published February 8, 2023 | Version 1
Dataset Open

A spatio-temporal dataset on food flows for four West African cities

  • 1. University of British Columbia, University of Kassel, University of Freiburg
  • 2. University of Kassel
  • 3. International Water Management Institute (IWMI)
  • 4. University for Development Studies
  • 5. Université de Dédougou, Dédougou
  • 6. 7 Strategic Humanitarian Services (Shumas)
  • 7. Institut d'Economie Rurale (IER)
  • 8. 9 Forstliche Versuchs- und Forschungsanstalt Baden-Württemberg

Description

Gaining insight into the food sourcing practices of cities is important to understand their resilience to climate change, economic crisis, as well as pandemics affecting food supply and security. To fill existing knowledge gaps in this area food flow data were collected in West Africa for four cities - Bamako (Mali), Bamenda (Cameroon), Ouagadougou (Burkina Faso), and Tamale (Ghana). The data covers, depending on the city, road, rail, boat, and air traffic. Surveys were conducted for one week on average during the peak harvest, lean, and rainy seasons, resulting in a dataset of over 100,000 entries for 46 unprocessed food commodities. The data collected includes information on the key types of transportation used, and quantity, source, and destination of the food flows. The data were used to delineate urban foodsheds and to identify city-specific factors constraining rural-urban linkages. They can be used to inform academic and policy discussions on urban food system sustainability, to validate other datasets, and to plan humanitarian aid and food security interventions.

Workflow and supplementary information associated with this dataset are found on GitHub (https://zenodo.org/record/7813686#.ZDQmKvbP23A). The data paper provides information on how data were collected and processed as well as how to use the data (https://www.nature.com/articles/s41597-023-02163-6): Karg, H., Akoto-Danso, E.K., Amprako, L. et al. A spatio-temporal dataset on food flows for four West African cities. Sci Data 10, 263 (2023). https://doi.org/10.1038/s41597-023-02163-6

 

 

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