Using ABM to Study the Potential of Land Use Change for Mitigation of Food Deserts

Asmamaw A. Gebrehiwot (), Leila Hashemi-Beni, Lyubov A. Kurkalova, Chyi L. Liang and Manoj K. Jha
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Asmamaw A. Gebrehiwot: Department of Built Environment, North Carolina A & T State University, Greensboro, NC 27411, USA
Leila Hashemi-Beni: Department of Built Environment, North Carolina A & T State University, Greensboro, NC 27411, USA
Lyubov A. Kurkalova: Department of Economics, North Carolina A & T State University, Greensboro, NC 27411, USA
Chyi L. Liang: Department of Agribusiness Econ Agriscience, North Carolina A & T State University, Greensboro, NC 27411, USA
Manoj K. Jha: Department of Civil, Architectural and Environmental Engineering, North Carolina A & T State University, Greensboro, NC 27411, USA

Sustainability, 2022, vol. 14, issue 15, 1-23

Abstract: Land-use transition is one of the most profound human-induced alterations of the Earth’s system. It can support better land management and decision-making for increasing the yield of food production to fulfill the food needs in a specific area. However, modeling land-use change involves the complexity of human drivers and natural or environmental constraints. This study develops an agent-based model (ABM) for land use transitions using critical indicators that contribute to food deserts. The model’s performance was evaluated using Guilford County, North Carolina, as a case study. The modeling inputs include land covers, climate variability (rainfall and temperature), soil quality, land-use-related policies, and population growth. Studying the interrelationships between these factors can improve the development of effective land-use policies and help responsible agencies and policymakers plan accordingly to improve food security. The agent-based model illustrates how and when individuals or communities could make specific land-cover transitions to fulfill the community’s food needs. The results indicate that the agent-based model could effectively monitor land use and environmental changes to visualize potential risks over time and help the affected communities plan accordingly.

Keywords: agent-based model; geospatial computational modeling; land use transition; food security (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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