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Mutual analyses of agriculture land use and transportation networks: The future location of soybean and corn production in Brazil

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  • Branco, José Eduardo Holler
  • Bartholomeu, Daniela Bacchi
  • Alves Junior, Paulo Nocera
  • Caixeta Filho, José Vicente

Abstract

Given the need to expand food production to satisfy an increasing world population; regional land-use planners must direct this expansion to available, permitted areas (i.e., not legally protected forests) where production can be maximized and transportation costs, production costs and environmental impacts can be minimized. In this balancing act, the capabilities and layout of the current and future transport system are crucial in determining the spatial distribution of future agricultural production.

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  • Branco, José Eduardo Holler & Bartholomeu, Daniela Bacchi & Alves Junior, Paulo Nocera & Caixeta Filho, José Vicente, 2021. "Mutual analyses of agriculture land use and transportation networks: The future location of soybean and corn production in Brazil," Agricultural Systems, Elsevier, vol. 194(C).
  • Handle: RePEc:eee:agisys:v:194:y:2021:i:c:s0308521x21002171
    DOI: 10.1016/j.agsy.2021.103264
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    References listed on IDEAS

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    1. K. Raju & D. Kumar, 2006. "Ranking Irrigation Planning Alternatives Using Data Envelopment Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(4), pages 553-566, August.
    2. Rachael D. Garrett & Meredith Niles & Juliana Gil & Philip Dy & Julio Reis & Judson Valentim, 2017. "Policies for Reintegrating Crop and Livestock Systems: A Comparative Analysis," Sustainability, MDPI, vol. 9(3), pages 1-22, March.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    5. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    8. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    9. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    10. Liu, Wenbin & Zhou, Zhongbao & Ma, Chaoqun & Liu, Debin & Shen, Wanfang, 2015. "Two-stage DEA models with undesirable input-intermediate-outputs," Omega, Elsevier, vol. 56(C), pages 74-87.
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    Cited by:

    1. Yang, Shuhui & Li, Zhongkai & Zhou, Jianlin & Gao, Yancheng & Cui, Xuefeng, 2024. "Evolving patterns of agricultural production space in China: A network-based approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(1), pages 121-134.
    2. Xinhai Lu & Jiao Hou & Yifeng Tang & Ting Wang & Tianyi Li & Xupeng Zhang, 2022. "Evaluating the Impact of the Highway Infrastructure Construction and the Threshold Effect on Cultivated Land Use Efficiency: Evidence from Chinese Provincial Panel Data," Land, MDPI, vol. 11(7), pages 1-20, July.
    3. Yu Chen & Wenhui Zhang & Yilian Liu & Weisong Li & Chengwu Liu & Shengfu Yang, 2023. "Spatial Pattern of Large-Scale Agricultural Land and Spatial Heterogeneity of Influencing Factors in the Mountainous Areas of Western China—Wuling Mountains as an Example," Land, MDPI, vol. 12(11), pages 1-26, November.
    4. Bruno Benzaquen Perosa & Ramon Felipe Bicudo da Silva & Mateus Batistella, 2024. "Market Access and Agricultural Diversification: An Analysis of Brazilian Municipalities," Land, MDPI, vol. 13(1), pages 1-13, January.

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