Advanced Search
MyIDEAS: Login to save this article or follow this journal

Generating crop sequences in land-use models using maximum entropy and Markov chains

Contents:

Author Info

  • Aurbacher, Joachim
  • Dabbert, Stephan

Abstract

Farm management models often produce average crop shares over a number of years, whereas models from the natural sciences often require inputs of sequences of crops grown on a specific field over several years. In interdisciplinary modelling, this difference can be a relevant obstacle. To bridge this gap, an approach is presented that allows disaggregating results from farm management models to the level required by many natural science models. The approach presented includes two methodological innovations: first, minimum cross entropy is used to ensure a unique solution when modelling a linear programming model at the field level, even when objective and constraint coefficients are identical for different fields. Second, the use of a calibrated Markov chain approach allows the creation of land-use sequences that are closer to the linear programming model's results than an unconditional stochastic simulation would be. The calibrated Markov chain makes use of a prior matrix of transition probabilities that can be empirically derived. Both simulations and analytical calculations with case study data show that the variances of the Markov chain approach are systematically lower than those yielded by a simple stochastic simulation approach. The approach introduced in this paper can improve the coupling of farm-level economic models with natural science models at the field level.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.sciencedirect.com/science/article/pii/S0308521X11000424
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Elsevier in its journal Agricultural Systems.

Volume (Year): 104 (2011)
Issue (Month): 6 (July)
Pages: 470-479

as in new window
Handle: RePEc:eee:agisys:v:104:y:2011:i:6:p:470-479

Contact details of provider:
Web page: http://www.elsevier.com/locate/agsy

Related research

Keywords: Maximum entropy Markov chains Farm management Linear programming Crop rotation Land use modelling;

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2009. "Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach," Agricultural Systems, Elsevier, vol. 99(2-3), pages 126-140, February.
  2. Schreinemachers, Pepijn & Berger, Thomas & Aune, Jens B., 2007. "Simulating soil fertility and poverty dynamics in Uganda: A bio-economic multi-agent systems approach," Ecological Economics, Elsevier, vol. 64(2), pages 387-401, December.
  3. Kachele, H. & Dabbert, S., 2002. "An economic approach for a better understanding of conflicts between farmers and nature conservationists--an application of the decision support system MODAM to the Lower Odra Valley National Park," Agricultural Systems, Elsevier, vol. 74(2), pages 241-255, November.
  4. You, Liangzhi & Wood, Stanley, 2006. "An entropy approach to spatial disaggregation of agricultural production," Agricultural Systems, Elsevier, vol. 90(1-3), pages 329-347, October.
  5. Lant, Christopher L. & Kraft, Steven E. & Beaulieu, Jeffrey & Bennett, David & Loftus, Timothy & Nicklow, John, 2005. "Using GIS-based ecological-economic modeling to evaluate policies affecting agricultural watersheds," Ecological Economics, Elsevier, vol. 55(4), pages 467-484, December.
  6. Oglethorpe, David R. & Sanderson, Roy A., 1999. "An ecological-economic model for agri-environmental policy analysis," Ecological Economics, Elsevier, vol. 28(2), pages 245-266, February.
  7. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
  8. van Wenum, J. H. & Wossink, G. A. A. & Renkema, J. A., 2004. "Location-specific modeling for optimizing wildlife management on crop farms," Ecological Economics, Elsevier, vol. 48(4), pages 395-407, April.
  9. Meyer-Aurich, Andreas, 2005. "Economic and environmental analysis of sustainable farming practices - a Bavarian case study," Agricultural Systems, Elsevier, vol. 86(2), pages 190-206, November.
  10. Castellazzi, M.S. & Wood, G.A. & Burgess, P.J. & Morris, J. & Conrad, K.F. & Perry, J.N., 2008. "A systematic representation of crop rotations," Agricultural Systems, Elsevier, vol. 97(1-2), pages 26-33, April.
  11. Martin Schönhart & Erwin Schmid & Uwe A. Schneider, 2009. "CropRota – A Model to Generate Optimal Crop Rotations from Observed Land Use," Working Papers 452009, Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Life Sciences, Vienna.
  12. Vermaat, Jan E. & Eppink, Florian & van den Bergh, Jeroen C.J.M. & Barendregt, Aat & van Belle, Jasper, 2005. "Aggregation and the matching of scales in spatial economics and landscape ecology: empirical evidence and prospects for integration," Ecological Economics, Elsevier, vol. 52(2), pages 229-237, January.
  13. Richard Howitt & Arnaud Reynaud, 2003. "Spatial disaggregation of agricultural production data using maximum entropy," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 30(3), pages 359-387, September.
  14. Detlefsen, Nina K. & Jensen, Allan Leck, 2007. "Modelling optimal crop sequences using network flows," Agricultural Systems, Elsevier, vol. 94(2), pages 566-572, May.
  15. Haneveld, W. K. Klein & Stegeman, A. W., 2005. "Crop succession requirements in agricultural production planning," European Journal of Operational Research, Elsevier, vol. 166(2), pages 406-429, October.
  16. Zeyuan Qiu, 2005. "Using Multi-Criteria Decision Models to Assess the Economic and Environmental Impacts of Farming Decisions in an Agricultural Watershed," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 27(2), pages 229-244.
  17. Raja Chakir, 2009. "Spatial Downscaling of Agricultural Land-Use Data: An Econometric Approach Using Cross Entropy," Land Economics, University of Wisconsin Press, vol. 85(2), pages 238-251.
  18. Zander, P. & Kachele, H., 1999. "Modelling multiple objectives of land use for sustainable development," Agricultural Systems, Elsevier, vol. 59(3), pages 311-325, March.
  19. Sorel, Luc & Viaud, Valérie & Durand, Patrick & Walter, Christian, 2010. "Modeling spatio-temporal crop allocation patterns by a stochastic decision tree method, considering agronomic driving factors," Agricultural Systems, Elsevier, vol. 103(9), pages 647-655, November.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Salassi, Michael E. & Deliberto, Michael A. & Guidry, Kurt M., 2013. "Economically optimal crop sequences using risk-adjusted network flows: Modeling cotton crop rotations in the southeastern United States," Agricultural Systems, Elsevier, vol. 118(C), pages 33-40.
  2. Aurbacher, Joachim & Parker, Phillip S. & Calberto Sánchez, Germán A. & Steinbach, Jennifer & Reinmuth, Evelyn & Ingwersen, Joachim & Dabbert, Stephan, 2013. "Influence of climate change on short term management of field crops – A modelling approach," Agricultural Systems, Elsevier, vol. 119(C), pages 44-57.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:104:y:2011:i:6:p:470-479. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.