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Simulating Agricultural Land Use Changes in Uganda Using an Agent-Based Model

  • Conference paper
Book cover Geo-Informatics in Resource Management and Sustainable Ecosystem (GRMSE 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 482))

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Abstract

Agent based modeling, a processed based approach, is advantageous in simulating the interaction between human’s decision processes and environmental systems. In this study, we apply an agent-based model to simulate potential agricultural land use change scenarios in Uganda. The simulation model incorporates decision making processes at small holder and commercial farmers’ level on the basis of biophysical and socioeconomic factors and use these as basis to analyze how farmers’ decisions may affect agricultural land use changes. Geographic information system (GIS) tools are employed to build spatial relations between farmer agents and land cover system. Satellite imageries are used to represent the initial land cover condition and serve as observed land cover dataset to calibrate the simulated results. The results of the simulation model are promising and the model was successful at representing historical and future scenarios of agricultural land use patterns at national-level.

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Author information

Authors and Affiliations

  1. Department of Geography and Environmental Resources, Southern Illinois University, IL, 62901, USA

    Jingjing Li

  2. Research Center on Health Disparities, Equity, and the Exposome, University of Tennessee at Memphis, 66 Pauline Suite 300, Memphis, TN, 38105, USA

    Tonny J. Oyana

Authors
  1. Jingjing Li
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  2. Tonny J. Oyana
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Editor information

Editors and Affiliations

  1. Wuhan University, China

    Fuling Bian

  2. Institute for Geospatial Research and Education, Eastern Michigan University, 125 King Hall, 48197, Ypsilanti, Michigan, USA

    Yichun Xie

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Li, J., Oyana, T.J. (2015). Simulating Agricultural Land Use Changes in Uganda Using an Agent-Based Model. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2014. Communications in Computer and Information Science, vol 482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45737-5_46

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  • DOI: https://doi.org/10.1007/978-3-662-45737-5_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45736-8

  • Online ISBN: 978-3-662-45737-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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