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Geneticland: Modelling Land-Use Change Using Evolutionary Algorithms

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Modelling Land-Use Change

Part of the book series: The GeoJournal Library ((GEJL,volume 90))

Abstract

Future land-use configurations provide valuable knowledge for policy makers and economic agents, especially under expected environmental changes such as decreasing rainfall or increasing temperatures. This chapter proposes an optimisation approach for modelling land-use change in which landscapes (land uses) are generated through the use of an evolutionary algorithm called GeneticLand. It is designed for a multiobjective function that aims at the minimisation of soil erosion and the maximisation of carbon sequestration, under a set of local restrictions. GeneticLand has been applied to a Mediterranean landscape, located in southern Portugal. The algorithm design and the results obtained show the feasibility of the generated landscapes, the appropriateness of the evolutionary methods to model land-use changes and the spatial characteristics of the landscape solutions that emerge when physical drivers have a major influence on their evolution.

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References

  • Beven, K. (2000) Rainfall-Runoff Modelling, The Primer, John Wiley & Sons, Chichester.

    Google Scholar 

  • Deb, K. (2001) Multi-Objective Optimization using Evolutionary Algorithms, John Wiley and Sons, Ltd, Chichester.

    Google Scholar 

  • Ducheyne, E. (2003) Multiple Objective Forest Management using GIS and Genetic Optimization Techniques, PhD Thesis, University of Gent, Gent.

    Google Scholar 

  • European Environment Agency (2005) Vulnerability and Adaptation to Climate Change in Europe, EEA Technical Report no. 7/2005, July. http://reports.eea.eu.int/ technical_report_2005_1207_144937/en.

    Google Scholar 

  • Instituto do Ambiente (2003) Programa Nacional para as Alterações Climáticas, Vol. 8: Florestas e Produtos Florestais Instituto do Ambiente, Faculdade de Ciências e Tecnologia, CEEETA, Lisboa.

    Google Scholar 

  • Knowles, J.D. and Corne, D.W. (1999) The Pareto Archived Evolution Strategy: A New Baseline Algorithm for Pareto Multiobjective Optimisation, in Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), Volume 1, pp. 98–105.

    Article  Google Scholar 

  • Lencastre, A. and Franco, F.M. (1992) Lições de hidrologia, New University of Lisbon Editorial Services, Lisbon.

    Google Scholar 

  • Maroco, J.P., Breia, E., Faria, T., Pereira, J.S. and Chaves, M.M. (2002) Effects of long-term exposure to elevated CO2 and N fertilization on the development of photosynthetic capacity and biomass accumulation in Quercus suber L, Plant Cell and Environment, 25 (1): 105–113.

    Article  Google Scholar 

  • McCarthy, J., Canziani, O., Leary, N., Dokken, D., and White, K. (2001) Climate Change 2001: Impacts, Adaptation, and Vulnerability, Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.

    Google Scholar 

  • McGarigal, K., and Marks, B.J. (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure, USDA For. Serv. Gen. Tech. Rep. PNW-351.

    Google Scholar 

  • Mühlenbein, H. (1992) How Genetic Algorithms Really Work: Mutation and Hillclimbing. in Männer, R. and Manderick, B. (eds) Parallel Problem Solving from Nature, Elsevier Science, Amsterdam, pp. 15–25.

    Google Scholar 

  • Nakicenovic, N., Alcamo, J., Davis, G., de Vries, B., Fehann, J., Gaffin, S., Gregory, K., Grubber, A., Jung, T.Y., Kram, T., Emilio, la Rovere, E., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L., Riahi, K., Roehrl, A., Rogner, H., Sankovski, A., Schelesinger, M.E., Shukla, P.R., Smith, S., Swart, R.J., van Rooyen, S. Victor, N. and Dadi, Z. (2000) Special Report, on Emissions Scenarios, Cambridge University Press, Cambridge.

    Google Scholar 

  • Nicolau, M.R.R.C. (2002) Modelação e mapeamento da distribuição espacial de precipitação – uma aplicação a Portugal continental, PhD Thesis, Faculty of Sciences and Technology, New University of Lisbon.

    Google Scholar 

  • Pimenta, M.T. (1998) Directrizes para a aplicação da Equação Universal de Perda dos Solos em SIG: factor de cultura C e factor de erodibilidade do solo K, INAG, Lisbon.

    Google Scholar 

  • Pongthanapanich, T. (2003) Review of Mathematical Programming for Coastal Land Use Optimization. University of Southern Denmark, Department of Environmental and Business Economics IME Working Paper 52/03.

    Google Scholar 

  • Qian, B., Corte-Real, J. and Xu, H. (2002) Multisite stochastic weather models for impact studies, International Journal of climatology, 22: 1377–1397.

    Article  Google Scholar 

  • Rounsevell, M., Ewert, D.A.F., Reginster, I., Leemans, R. and Carter, T.R. (2005) Future Scenarios of European agricultural land use. II. Projecting changes in cropland and grassland, Agriculture Ecosystems & Environment, 107(2–3): 117–135.

    Article  Google Scholar 

  • Schwefel, H.P. (1981) Numerical Optimization of Computer Models, John Wiley & Sons, Chichester.

    Google Scholar 

  • Tognetti, R., Johnson, J.D., Michelozzi, M. and Raschi, A. (1998) Response of foliar metabolism in mature trees of Quercus pubescens and Quercus ilex to long-term elevated CO2, Environmental and Experimental Botany, 39: 233–245.

    Article  Google Scholar 

  • Tognetti, R., Minnocci, A., Peñuelas, J., Rasci, A. and Jones, M.B. (2000) Comparative field water relations of three Mediterranean shrub species co-occuring at a natural CO2 vent, Journal of Experimental Botany, 51(347): 1135–1146.

    Article  Google Scholar 

  • Tognetti, R., Sebastiani, L., Vitagliano, C., Raschi, A. and Minnocci, A. (2001) Responses of two olive tree (Olea europaea L.) cultivars to elevated CO2 concentration in the field, Photosynthetica, 39(3): 403–410.

    Article  Google Scholar 

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Seixas, J., Nunes, J., Lourenço, P., Corte-Real, J. (2007). Geneticland: Modelling Land-Use Change Using Evolutionary Algorithms. In: Koomen, E., Stillwell, J., Bakema, A., Scholten, H.J. (eds) Modelling Land-Use Change. The GeoJournal Library, vol 90. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5648-2_11

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