Modeling Agricultural Change through Logistic Regression and Cellular Automata: A Case Study on Shifting Cultivation


Agricultural expansion is one of the prime driving forces of global land cover change. Despite the increasing attention to the factors that cause it, the patterns and processes associated with indigenous cultivation systems are not well understood. This study analyzes agricultural change associated with subsistence-based indigenous production systems in the lower Pastaza River Basin in the Ecuadorian Amazon through a spatially explicit dynamic model. The model integrates multiple logistic regression and cellular automata to simulate agricultural expansion at a resolution consistent with small scale agriculture and deal with inherently spatial processes. Data on land use and cultivation practices were collected through remote sensing and field visits, and processed within a geographic information system framework. Results show that the probability of an area of becoming agriculture increases with population pressure, in the vicinity of existing cultivation plots, and proximity to the center of human settlements. The positive association between proximity to cultivation areas and the probability of the presence of agriculture clearly shows the spillover effect and spatial inertia carried by shifting cultivation practices. The model depicts an ideal shifting cultivation system, with a complete cropping-fallow-cropping cycle that shows how agricultural areas expand and contract across space and over time. The model produced relatively accurate spatial outputs, as shown by the results of a spatial comparison between the simulated landscapes and the actual one. The study helped understand local landscape dynamics associated with shifting cultivation systems and their implications for land management.

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Lopez, S. (2014) Modeling Agricultural Change through Logistic Regression and Cellular Automata: A Case Study on Shifting Cultivation. Journal of Geographic Information System, 6, 220-235. doi: 10.4236/jgis.2014.63021.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Verburg, P., Neumann, K. and Nol, L. (2011) Challenges in Using Land Use and Land Cover Data for Global Change Studies. Global Change Biology, 17, 974-989.
[2] Turner II, B.L. and Robbins, P. (2008) Land-Change Science and Political Ecology: Similarities, Differences, and Implications for Sustainable Science. The Annual Review of Environment and Resources, 33, 295-316.
[3] Chomitz, K. (2007) At Loggerheads? Agricultural Expansion, Poverty Reduction, and Environment in the Tropical Forests. World Bank Policy Research Report 308. World Bank, Washington DC.
[4] DeFries, R.S., Rudel, T., Uriarte, M. and Hansen, M. (2010) Deforestation Driven by Urban Population Growth and Agricultural Trade in the Twenty-First Century. Nature Geoscience, 3, 178-181.
[5] Gray, C.L., Bilsborrow, R.E., Bremner, J.L. and Lu, F. (2008) Indigenous Land Use in the Ecuadorian Amazon: A Cross-Cultural and Multilevel Analysis. Human Ecology, 36, 97-109.
[6] Onojeghuo, A. and Blackburn, A. (2011) Forest Transition in an Ecologically Important Region: Patterns and Causes for Landscape Dynamics in the Niger Delta. Ecological Indicators, 11, 1437-1446.
[7] LaGro Jr., J.A. and DeGloria, S.D. (1992) Land Use Dynamics within an Urbanizing Non-Metropolitan County in New York State (USA). Landscape Ecology, 7, 275-289.
[8] Rudel, T.K. (2009) Sociological Perspective on Suburban Sprawl and Tropical Deforestation. American Journal of Sociology, 115, 129-154.
[9] Moran, E.F. and Brondizio, E.S. (1998) Land Use Change after Deforestation in Amazonia. In: Liverman, D., Moran, E., Rindfuss, F. and Stern, P.C., Eds., People and Pixels: Linking Remote Sensing and Social Science, National Academy Press, Washington DC, 94-120.
[10] Mena, C.F., Barbieri, A.F., Walsh, S.J., Erlien, C.M., Holt, F.L. and Bilsborrow, R.E. (2006) Pressure on the Cuyabeno Wildlife Reserve: Development and Land Use/Cover Change in the Northern Ecuadorian Amazon. World Development, 34, 1831-1849.
[11] VanWey, L., Gilvan, G. and D’Antona, A. (2012) Out-Migration and Land-Use Change in Agricultural Frontiers: Insights from Altamira Settlement Project. Population and Environment, 34, 44-68.
[12] Chomitz, K.M. and Gray, D.A. (1996) Roads, Land Use and Deforestation: A Spatial Model Applied to Belize. World Bank Economic Review, 10, 487-512.
[13] Mertens, B. and Lambin, E.F. (2000) Land-Cover-Change Trajectories in Southern Cameroon. Annals of the Association of American Geographers, 90, 467-494.
[14] Southworth, J., Marsik, M., Qiu, Y., Perz, S., Gumming, G., Stevens, F., Rocha, K., Duchelle, A. and Barnes, G. (2011) Roads as Drivers of Change: Trajectories across the Tri-National Frontier in MAP, the Southwestern Amazon. Remote Sensing, 3, 1047-1066.
[15] Nelson, G.C., Harris, V. and Stone, S.W. (2001) Deforestation, Land Use, and Property Rights: Empirical Evidence from Darien, Panama. Land Economics, 77, 187-205.
[16] Wunder, S. and Sunderlin, W.D. (2004) Oil, Macroeconomics, and Forests: Assessing the Linkages. World Bank Research Observer, 19, 231-257.
[17] Brondizio, E., McCraken, S., Moran, E., Siqueira, A., Nelson, D. and Rodriguez-Pedraza, C. (2002) The Colonist Footprint. In: Wood, C.H. and Porro, R., Eds., Deforestation and Land Use in the Amazon, University of Florida Press, Gainesville, 133-161.
[18] Castro, M. and Singer, B. (2012) Agricultural Settlement and Soil Quality in the Brazilian Amazon. Population & Environment, 34, 22-43.
[19] Nagendra, H., Southworth, J. and Tucker, C. (2003) Accessibility as a Determinant of Landscape Transformation in Western Honduras: Linking Pattern and Process. Landscape Ecology, 18, 141-158.
[20] Lopez, S. and Sierra, R. (2010) Agricultural Change in the Pastaza River Basin: A Spatially Explicit Model of Native Amazonian Cultivation. Applied Geography, 30, 355-369.
[21] Parker, D.C., Manson, S.M., Janssen, M.A., Hoffman, M.J. and Deadman, P. (2003) Multi-Agent System Models for the Simulation of Land-Use and Land-Cover Change: A Review. Annals of the Association of American Geographers, 93, 314-337.
[22] Liverman, D., Moran, E.F., Rindfuss, R. and Stern, P.C. (Eds.) (1998) People and Pixels: Linking Remote Sensing and Social Science. National Academy Press, Washington DC.
[23] Liu, J., Dietz, T., Carpenter, S.R., Folke, C., Alberti, M., Redman, C.L., Schneider, S.H., Ostrom, E., Pell, A.N., Lubchenco, J., Taylor, W.W., Ouyang, Z., Deadman, P., Kratz, T. and Provencher, W. (2007) Coupled Human and Natural Systems. AMBIO: A Journal of the Human Environment, 36, 639-649.
[24] Hegselmann, R. (1998) Modeling Social Dynamics by Cellular Automata. In: Jackson, W.B.G., Liebrand, M., Nowak, A. and Hegselmann, R., Eds., Computer Modeling of Social Processes, Sage, London, 37-64.
[25] Messina, J.P. and Walsh, S.J. (2001) 2.5D Morphogenesis: Modeling Landuse and Landcover Dynamics in the Ecuadorian Amazon. Plant Ecology, 156, 75-88.
[26] Hernandez-Encinas, A., Hernandez-Encinas., L., Hoya-White, S., del Rey, A.M. and Rodríguez-Sánchez, G. (2007) Simulation of Forest Fire Fronts Using Cellular Automata. Advances in Numerical Methods for Environmental Engineering, 38, 372-378.
[27] Colasanti, R.L., Hunt, R. and Watrud, L. (2007) A Simple Cellular Automaton Model for High-Level Vegetation Dynamics. Ecological Modelling, 203, 363-374.
[28] White, R. and Engelen, G. (1993) Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns. Environment and Planning A, 25, 1175-1199.
[29] Wu, F. (1998) SimLand: A Prototype to Simulate Land Conversion through the Integrated GIS and CA with AHP-Derived Transition Rules. International Journal of Geographical Information Science, 12, 63-82.
[30] de Almeida, C.M., Batty, M., Vieira Monteiro, A., Camara, G., Soares-Filho, B., Cerqueira, G.C. and Lopes, C. (2003) Stochastic Cellular Automata Modeling of Urban Land Use Dynamics: Empirical Development and Estimation. Computers, Environment, and Urban Systems, 27, 481-509.
[31] Van Vliet, J., White, R. and Dragicevic, S. (2009) Modeling Urban Growth Using a Variable Grid Cellular Automaton. Computers, Environment, and Urban Systems, 33, 35-43.
[32] Garcia, C.V., Woodard, P.M., Titus, S.J., Adamowicz, W.L. and Lee, B.S. (1995) Alogit Model for Predicting the Daily Occurrence of Human Caused Forest-Fires. International Journal of Wildland Fire, 5, 101-111.
[33] Serneels, S. and Lambin, E.F. (20010 Proximate Causes of Land-Use Change in Narok District, Kenya: A Spatial Statistical Model. Agriculture, Ecosystems, and Environment, 85, 65-81.
[34] Lin, Y., Chu, H., Wu, C. and Verburg, P. (2010) Predictive Ability of Logistic Regression, Auto-Logistic Regression and Neural Network Models in Empirical Land-Use Change Modeling—A Case Study. International Journal of Geographical Information Science, 25, 65-87.
[35] Ludeke, A.K., Maggion, R.C. and Reid, L.M. (1990) An Analysis of Anthropogenic Deforestation Using Logistic Regression and GIS. Journal of Environmental Management, 31, 247-259.
[36] De Almeida, C.M., Gleriani, J.M., Castejon, E.F. and Soares-Filho, B.S. (2008) Using Neural Networks and Cellular Automata for Modelling Intra-Urban Land-Use Dynamics. International Journal of Geographical Information Science, 22, 943-963.
[37] Hosmer, D.W. and Lemeshow, S. (2000) Applied Logistic Regression. 2nd Edition, John Wiley & Sons Inc., Hoboken.
[38] Wu, F. (2002) Calibration of Stochastic Cellular Automata: The Application to Rural-Urban Land Conversions. International Journal of Geographical Information Science, 16, 795-818.
[39] Soares-Filho, B.S., Cerqueira, G.C. and Pennachin, C.L. (2002) DINAMICA—A Stochastic Cellular Automata Model Designed to Simulate the Landscape Dynamics in an Amazonian Colonization Frontier. Ecological Modeling, 154, 217-235.
[40] Verburg, P.H., Soepboer, W., Veldkamp, A., Limpiada, R., Espaldon, V. and Mastura, S. (2002) Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model. Environmental Management, 30, 391-405.
[41] Zhu, Z., Liu, L., Chen, Z., Zhang, J. and Verburg, P.H. (2009) Land-Use Change Simulation and Assessment of Driving Factors in the Loess Hilly Region—A Case Study as Pengyang County. Environmental Monitoring and Assessment, 164, 133-142.
[42] Liu, Y. and Feng, Y. (2012) A Logistic Based Cellular Automata Model for Continuous Urban Growth Simulation: A Case Study of the Gold Coast City, Australia. In: Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M., Eds., Agent-Based Models of Geographical Systems, Springer, Netherlands, 643-662.
[43] Walsh, S.J., Messina, J.P., Mena, C.F., Malanson, G.P. and Page, P.H. (2008) Complexity Theory, Spatial Simulation Models, and Land Use Dynamics in the Northern Ecuadorian Amazon. Geoforum, 39, 867-878.
[44] INEC (2014) Instituto Nacional de Estadísticas y Censos.
[45] Lopez, S., Beard, R. and Sierra, R. (2013) Landscape Change in Western Amazonia. Geographical Review, 103, 37-58.
[46] METI and NASA (2009) Global Elevation Digital Map.
[47] Custode, E. (1983) Mapas morfopedológicos de las provincias de Pastaza y Morona Santiago. PRONAREG-ORSTOM, Ministerio de Agricultura y Ganadería, Quito.
[48] Maeda, E.E., De Almeida, C.M., De Carvalho Ximenes, A., Formaggio, A.R., Shimabukuro, Y.E. and Pellikka, P. (2011) Dynamic Modeling of Forest Conversion: Simulation of Past and Future Scenarios of Rural Activities Expansion in the Fringes of the Xingu National Park, Brazilian Amazon. International Journal of Applied Earth Observation and Geoinformation, 13, 435-446.
[49] Dale, V.H., O’neill, R.V., Southworth, F. and Pedlowski, M. (1994) Modeling Effects of Land Management in the Brazilian Amazonian Settlement of Rondonia. Conservation Biology, 8, 196-206.
[50] Frohn, R.C., Mcgwire, K.C., Dale, V.H. and Estes, J.E. (1996) Using Satellite Remote Sensing Analysis to Evaluate a Socio-Economic and Ecological Model of Deforestation in Rondonia, Brazil. International Journal of Remote Sensing, 17, 3233-3255.
[51] Carlson, K.M., Curran, L.M., Ratnasari, D., Pittman, A.M., Soares-Filho, B.S., Asner, G.P., Trigg, S.N., Gaveau, D.A., Lawrence, D. and Rodrigues, H.O. (2012) Committed Carbon Emissions, Deforestation, and Community Land Conversion from Oil Palm Plantation Expansion in West Kalimantan, Indonesia. Proceedings of the National Academy of Sciences of the United States of America, 109, 7559-7564.
[52] Haines-Young, R. and Chopping, M. (1996) Quantifying Landscape Structure: A Review of Landscape Indices and Their Application to Forested Landscapes. Progress in Physical Geography, 20, 418-445.
[53] McGarigal, K., Cushman, S.A., Neel, M.C. and Ene, E. (2002) FRAGSTATS v3: Spatial Pattern Analysis Program for Categorical Maps. Computer Software Program Produced by the Authors at the University of Massachusetts, Amherst.
[54] Stillwell, J. and Clarke, G. (2003) Applied GIS and Spatial Analysis. John Wiley & Sons, Hoboken.
[55] Turner, B.L., Hanham, R.Q. and Portataro, A.V. (1977) Population Pressure and Agricultural Intensity. Annals of the Association of American Geographers, 67, 383-396.
[56] Smith, J. (2001) Land Cover Assessment of Indigenous Communities in the BOSAWAS Region of Nicaragua. Human Ecology, 29, 339-347.
[57] Bilsborrow, R. and Geores, M. (1994) Population, land-Use, and the Environment in Developing Countries: What Can We Learn from Cross-National Data? In: Brown, K. and Pearce, D., Eds., The Causes of Tropical Deforestation, the Economic and Statistical Analysis of Factors Giving Rise to the Loss of Tropical Forests, University College London Press, London, 106-133.
[58] McSweeny, K. (2005) Indigenous Population Growth in the Lowland Neotropics: Social Science Insights for Biodiversity Conservation. Conservation Biology, 19, 1375-1384.
[59] McSweeny, K. and Arps, S. (2005) A “Demographic Turnaround”: The Rapid Growth of Indigenous Populations in Lowland Latin America. Latin American Research Review, 40, 3-29.

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