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A GIS-based agricultural land-use allocation model coupling increase and decrease in land demand

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  • Pilehforooshha, Parastoo
  • Karimi, Mohammad
  • Taleai, Mohammad

Abstract

Agricultural land use allocation involves assessment of land potential as well as land demand for various crops to identify the optimum land unit for each type. Current allocation models often focus on the perspective of increase in land demand. However, processes causing loss of arable land should be considered to correct the demand used in conventional allocation processes. In order to achieve that, a two stage model for crop allocation is presented which uses different models such as cellular automata, Markov chain, fuzzy rule-based system, goal programming and GIS raster analysis in a logical framework. In the presented model, at first by considering environmental (soil erosion and soil salinity) and economic (urban expansion) factors leading to arable land loss, agricultural use of each land unit is allocated. Next, crop types within the agricultural area are determined based on land suitability evaluation and demand assessment for each crop. This model is developed for rural land use planning on a regional scale and is applied to the Borkhar and Meymeh district in Isfahan province in Iran to predict land use map of 2015. The overall accuracy of 0.609 in the first step allowed us to draw conclusion that the inclusion of factors resulting farmland decline in allocation process gives more accurate results than the former allocation techniques which merely model factors causing increase in agricultural land areas. Moreover, according to the results for 2015, 27.82%, 21.64%, 7.27%, 5.85%, 7.36%, 6.36% and 1.74% of agricultural areas is allocated to wheat, wheat-maize, barley, barley-maize, maize, alfalfa and potato, respectively. The presented approach has advantageous to determine the crops with highest suitability for a given area according to the desired objectives.

Suggested Citation

  • Pilehforooshha, Parastoo & Karimi, Mohammad & Taleai, Mohammad, 2014. "A GIS-based agricultural land-use allocation model coupling increase and decrease in land demand," Agricultural Systems, Elsevier, vol. 130(C), pages 116-125.
    • Handle: RePEc:eee:agisys:v:130:y:2014:i:c:p:116-125
    DOI: 10.1016/j.agsy.2014.07.001
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    1. Michel Hagoort & Stan Geertman & Henk Ottens, 2008. "Spatial externalities, neighbourhood rules and CA land-use modelling," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 39-56, March.
    2. Sante, Ines & Crecente, Rafael, 2007. "LUSE, a decision support system for exploration of rural land use allocation: Application to the Terra Cha district of Galicia (N.W. Spain)," Agricultural Systems, Elsevier, vol. 94(2), pages 341-356, May.
    3. Aurbacher, Joachim & Dabbert, Stephan, 2011. "Generating crop sequences in land-use models using maximum entropy and Markov chains," Agricultural Systems, Elsevier, vol. 104(6), pages 470-479, July.
    4. Biswas, Animesh & Pal, Bijay Baran, 2005. "Application of fuzzy goal programming technique to land use planning in agricultural system," Omega, Elsevier, vol. 33(5), pages 391-398, October.
    5. Nisar Ahamed, T. R. & Gopal Rao, K. & Murthy, J. S. R., 2000. "GIS-based fuzzy membership model for crop-land suitability analysis," Agricultural Systems, Elsevier, vol. 63(2), pages 75-95, February.
    6. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    7. Xu, Xia & Gao, Qiong & Liu, Ying-Hui & Wang, Jing-Ai & Zhang, Yong, 2009. "Coupling a land use model and an ecosystem model for a crop-pasture zone," Ecological Modelling, Elsevier, vol. 220(19), pages 2503-2511.
    8. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    9. Ceballos-Silva, Alejandro & Lopez-Blanco, Jorge, 2003. "Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and land use/cover mapping: a case study in Central Mexico," Agricultural Systems, Elsevier, vol. 77(2), pages 117-136, August.
    10. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    11. Sicat, Rodrigo S. & Carranza, Emmanuel John M. & Nidumolu, Uday Bhaskar, 2005. "Fuzzy modeling of farmers' knowledge for land suitability classification," Agricultural Systems, Elsevier, vol. 83(1), pages 49-75, January.
    12. Reshmidevi, T.V. & Eldho, T.I. & Jana, R., 2009. "A GIS-integrated fuzzy rule-based inference system for land suitability evaluation in agricultural watersheds," Agricultural Systems, Elsevier, vol. 101(1-2), pages 101-109, June.
    13. Agrell, Per J. & Stam, Antonie & Fischer, Gunther W., 2004. "Interactive multiobjective agro-ecological land use planning: The Bungoma region in Kenya," European Journal of Operational Research, Elsevier, vol. 158(1), pages 194-217, October.
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