A GIS-based interactive map enabling data-driven decision-making in Nigeria's food supply chain

Divinefavour Odion; Kanaha Shoji; Roberta Evangelista; Joaquin Gajardo; Thomas Motmans; Thijs Defraeye; Daniel Onwude

doi:10.1016/j.mex.2023.102047

A GIS-based interactive map enabling data-driven decision-making in Nigeria's food supply chain

MethodsX. 2023 Feb 1:10:102047. doi: 10.1016/j.mex.2023.102047. eCollection 2023.

Authors

Divinefavour Odion¹, Kanaha Shoji², Roberta Evangelista³, Joaquin Gajardo², Thomas Motmans³, Thijs Defraeye², Daniel Onwude²

Affiliations

¹ Constructor University Bremen, Campus Ring 1, 28759 Bremen, Germany.
² Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland.
³ BASE, Basel Agency for Sustainable Energy, Elisabethenstrasse 22, Basel CH-4051, Switzerland.

Abstract

The accessibility of open-source data on fresh food supply chains provides key stakeholders from the public and private sectors with insights for better decision-making to drive food loss reduction. Nigeria has a fair amount of open-source agricultural and climate-related data. However, most of these datasets are not readily accessible. This paper presents a detailed method used to develop an interactive web Geographic Information System (GIS) tool that collates and visualizes available open-source datasets on Nigeria's Agricultural Sector with particular focus on the fresh produce supply chains. The following steps were used to create such an interactive map. •Open-source data were acquired in various forms, including tabular, vector, and rasters, processed and uploaded as layers on the interactive web map.•Most of the data needed some processing on open-source geographic information system applications and web-based computing platforms to transform them into sources of actionable insights•These final processed layers were then uploaded to a consolidated interactive web map built on the Google Earth Engine platform. The gathered open-source data includes crop production data, market prices, weather, road network, market locations, mobile coverage, water access, water scarcity, and food insecurity. The method described here also allows the reproduction of such maps for other countries.

Keywords: Cooling solution; Data visualization; Fresh produce; Google Earth Engine; Postharvest supply chain; Smallholders; Visualizing the potential for sustainable cooling solutions across Nigeria via an interactive web-GIS tool.