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.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Turner, B.L., William, B.M., David, L.S.: Global land-use/land-cover change: towards an integrated study. Ambio-Stockholm 23, 91–91 (1994)
Turner II, B.L., Lambin, E.F., Reenberg, A.: Land change science special feature: the emergence of land change science for global environmental change and sustainability. Proc. Natl Acad. Sci. 104, 20666–20671 (2007)
Bonan, G.B.: Effects of land use on the climate of the United States. Climatic Change 37(3), 449–486 (1997)
Pielke, R.A., Marland, S.G., Bets, R.A., Chase, T.N., Eastman, J.L., Neils, J.O., Niyogi, D.D.S., Running, S.: The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases. Philosophical Transactions of the Royal Society A 360, 1705–1719 (2002)
Manson, S.M.: Agent-based modeling and genetic programming for modeling land change in the Southern Yucatan Peninsular Region of Mexico. Agriculture, Ecosystems & Environment 111(1), 47–62 (2005)
Verburg, P.H., Schulp, C.J.E., Witte, N., Veldkamp, A.: Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agriculture, Ecosystems & Environment 114(1), 39–56 (2006)
Valbuena, D., Verburg, P.H., Bregt, A.K., Ligtenberg, A.: An agent-based approach to model land-use change at a regional scale. Landscape Ecology 25(2), 185–199 (2010)
Rindfuss, R.R., Walsh, S.J., Turner II, B.L., Fox, J., Mishra, V.: Developing a science of land change: challenges and methodological issues. PNAS 101, 13976–13981 (2004)
Beratan, K.K.: A cognition-based view of decision processes in complex social–ecological systems. Ecol. Soc. 12(1), 27 (2007)
Matthews, R.B., Gilbert, N.G., Roach, A., Polhill, J.G., Gotts, N.M.: Agent-based land-use models: a review of applications. Landscape Ecology 22(10), 1447–1459 (2007)
Macal, C.M., North, M.J.: Agent-based modeling and simulation. In: Winter Simulation Conference, pp. 86–98 (2009)
Valbuena, D., Verburg, P.H., Bregt, A.K.: A method to define a typology for agent-based analysis in regional land-use research. Agriculture, Ecosystems & Environment 128(1), 27–36 (2008)
Naivinit, W., Page, C.L., Trébuil, G., Gajaseni, N.: Participatory Agent-Based Modeling and Simulation of Rice Production and Labor Migrations in Northeast Thailand. Environmental Modelling & Software 25, 1345–1358 (2010)
Saqalli, M., Gérard, B., Bielders, C., Defourny, P.: Testing the Impact of Social Forces on the Evolution of Sahelian Farming Systems: A Combined Agent-Based Modeling and Anthropological Approach. Ecological Modelling 221, 2714–2727 (2010)
Acosta, L.A., Rounsevell, M.D.A., Bakker, M., Doorn, A.V., Gomez-Delgado, M., Delgado, M.: An Agent-Based Assessment of Land Use and Ecosystem Changes in Traditional Agricultural Landscape of Portugal. Intelligent Information Management 6, 55–80 (2014)
Mena, C.F., Walsh, S.J., Frizzelle, B.G., Yao, X.Z., Malanson, G.P.: Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model. Applied Geography 31, 210–222 (2011)
MAFAP (MONITORING AFRICAN FOOD AND AGRICULTURAL POLICIES).: Review of food and agricultural policies in Uganda. MAFAP Country Report Series, FAO, Rome, Italy (2013)
UBOS (Uganda Bureau of Statistics).: Statistical Abstract 2013. UBOS, Uganda (2013)
UBOS (Uganda Bureau of Statistics).: Statistical Abstract 2002. UBOS, Uganda (2002)
World borders dataset, http://thematicmapping.org/downloads/world_borders.php (accessed on June 24, 2014)
Benin, S., Thurlow, J., Diao, X., Kebba, A., Ofwono, N.: Agricultural growth and investment options for poverty reduction in Uganda. Intl. Food Policy Res. Inst. (2008)
UBOS (Uganda Bureau of Statistics).: Statistical Abstract 2002. UBOS, Uganda (2010)
MAAIF (Ministry of Agriculture, Animal Industry and Fisheries).: National Agriculture Policy 2011. Kampala, Uganda (2011)
FAO.: The State of Food Insecurity in World 2012 (2012)
IFPRI.: Agricultural growth and investment options for poverty reduction in Uganda. International Food Policy Research Institute (2007)
Landsat Satellite imageries for Uganda, http://earthexplorer.usgs.gov/USGS (accessed on February 9, 2014)
Digital Terrain Elevation Data, http://data.geocomm.com/catalog/UG/group121.html (accessed on March 5, 2014)
Lu, D., Weng, Q.: Urban classification using full spectral information of Landsat ETM+ imagery in Marion County, Indiana. Photogrammetric Engineering & Remote Sensing 71(11), 1275–1284 (2005)
Anderson, J.R.: A land use and land cover classification system for use with remote sensor data, vol. 964. US Government Printing Office (1976)
Jensen, J.R.: Introductory digital image processing: a remote sensing perspective, 3rd edn. Prentice-Hall Inc. (2005)
ERDAS Imagine. ERDAS Inc. Norcross, Geogia
Aerial Photos for Uganda, Imagery @ 2014 CNES/AstriumDigitalGlobe, Google Maps and Google Earth, http://maps.google.com (accessed on June 10, 2014)
Agent Analyst. ESRI Inc. Redlands, California
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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)