Modeling Land Change using One or Two Time Points based Calibration - A Comparison of Factors

María Teresa Camacho Olmedo

2017

Abstract

One of land change model parameters in calibration step relates to how changes over time and space are considered in the model. A land change model can be calibrated with the state at one time point or with the difference between two time points. The purpose is describing land use and cover (LUC) state patterns, i.e. one time point calibration, and LUC transition patterns, i.e. two time points. For a case study in Spain we obtained the collections of factors for two calibration periods at one time point (dates 2000 and 2006) and the collections of factors for two calibration periods between two time points (periods 1990-2000 and 2000-2006). Evidence likelihood is used to transform the explanatory variables into factors. The objective of this paper is to compare these four collections of factors to show how the choice of reference maps influences the factors and how these factors highlight the change patterns in two different calibration periods and in the calibration of two models. As a following step the detailed results for the different factors and LUC categories are analysed.

References

  1. Abuelaish, B., Camacho Olmedo, M.T., 2016. Scenario of land use and land cover change in the Gaza Strip using remote sensing and GIS models. Arab J Geosci (2016) 9:274.
  2. Camacho Olmedo M.T., Paegelow M., Mas, J.F., 2013. Interest in intermediate soft-classified maps in land change model validation: suitability versus transition potential. International Journal of Geographical Information Science 27 (12): 2343-2361.
  3. Camacho Olmedo, M.T., Pontius R.G. Jr., Paegelow M., Mas, J.F., 2015. Comparison of simulation models in terms of quantity and allocation of land change. Environmental Modelling & Software, 69 (2015): 214-221.
  4. Clark Labs, 2016. Available from: http://www.clarklabs.org/.
  5. Conway T.M., Wellen, C.C., 2011. Not developed yet? Alternative ways to include locations without changes in land use change models. International Journal of Geographical Information Science, 25 (10): 1613- 1631.
  6. NRC, 2013. Advancing Land Change Modeling: Opportunities and Research Requirements. Committee on Needs and Research Requirements for Land Change, Modeling; Geographical Sciences Committee; Board on Earth Sciences, and Resources; Division on Earth and Life Studies, National Research Council, Washington, USA.
  7. Eastman, J.R., Solorzano, L.A., Van Fossen M.E., 2005. Transition potential modeling for land cover change. In: Maguire, D.J., Batty, M., Goodchild, M.F. (eds.) GIS, spatial analysis, and modeling. Redland, CA: ESRI, pp 357-385.
  8. Gómez Espín, J.M., López Fernández, J.A., Montaner Salas, M.E., (eds.) 2011. Modernización de regadíos: Sostenibilidad social y económica. La singularidad de los regadíos del Trasvase Tajo-Segura. Colección Usos del agua en el territorio. Universidad de Murcia. Spain.
  9. Gómez, J.L., Grindlay, A. (eds.) 2008. Agua, Ingeniería y Territorio: La transformación de la cuenca del río Segura por la IngenieríaHidráulica. Ministerio de Medio Ambiente, Medio Rural y Marino. Confederación Hidrográfica del Segura. Spain.
  10. Kolb, M., Mas, J.F., Galicia, L., 2013. Evaluating drivers of land-use change and transition potential models in a complex lanscape in Southern Mexico. International Journal of Geographical Information Science 27(9):1804-1827.
  11. Lambin, E. et al., 2001. The causes of land-use and land cover change: moving beyond the myths. Global Environmental Change 11(4):261-269.
  12. Mas, J.F., Flamenco-Sandoval, A., 2011. Modelación de los cambios de coberturas/uso del suelo en una región tropical de México. GeoTrópico, 5(1):1-24.
  13. Mas, J.F., Kolb, M, Paegelow, M., Camacho Olmedo, M.T., Houet, T., 2014. Inductive pattern-based land use / cover change models: A comparison of four software packages. Environmental Modelling & Software, 51(2014): 94-111.
  14. Osorio, L.P., Mas, J.F., Guerra, F., Maass, M., 2015. Análisis y modelación de los procesos de deforestación: un caso de estudio en la cuenca del río Coyuquilla, Guerrero, México. Investigaciones Geográficas, Boletín, núm. 88:60-74.
  15. Paegelow, M., Camacho Olmedo, M.T., 2005. Possibilities and limits of prospective GIS land cover modeling - a compared case study: Garrotxes (France) and Alta Alpujarra Granadina (Spain). International Journal of Geographical Information Science, 19 (6):697-722.
  16. Paegelow M., Camacho Olmedo, M.T., (eds.) 2008. Modelling environmental dynamics. Advances in geomatics solutions. Berlin: Springer-Verlag.
  17. Paegelow M., Camacho Olmedo, M.T., Mas, J.F., Houet. T., 2014. Benchmarking of LUCC modelling tools by various validation techniques and error analysis. Cybergeo, document 701, mis en ligne le 22 décembre 2014.
  18. Pérez-Vega, A., Mas, J.F., Ligmann-Zielinska, A., 2012. Comparing two approaches to land use/cover change modeling and their implications for the assessment of biodiversity loss in a deciduous tropical forest. Environmental Modelling & Software 29 (1):11-23.
  19. Pontius, R.G.,Jr., Malanson, J., 2005. Comparison of the structure and accuracy of two land change models. International Journal of Geographical Information Science 19:243-265.
  20. Sangermano, F., Eastman, J.R., Zhu, H. 2010. Similarity weighted instance based learning for the generation of transition potentials in land change modeling. Transactions in GIS 14(5):569-580.
  21. Soares-Filho, B., Rodrigues, H., Follador, M., 2013. A hybrid analytical-heuristic method for calibrating landuse change models. Environmental Modelling & Software 43(2013):80-87.
  22. Villa, N., et al., 2007. Various approaches for predicting land cover in Mediterranean mountains. Communication in Statistics 36(1):73-86.
  23. Wang, J., Mountrakis, G., 2011. Developing a multinetwork urbanization model: a case study of urban growth in Denver, Colorado. International Journal of Geographical Information Science 25(2):229-253.
  24. Yu, J., et al., 2011. Cellular automata-based spatial multicriteria land suitability simulation for irrigated agriculture. International Journal of Geographical Information Science 25(1):131-148.
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Paper Citation


in Harvard Style

Camacho Olmedo M. (2017). Modeling Land Change using One or Two Time Points based Calibration - A Comparison of Factors . In Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GAMOLCS, ISBN 978-989-758-252-3, pages 341-349. DOI: 10.5220/0006384503410349


in Bibtex Style

@conference{gamolcs17,
author={María Teresa Camacho Olmedo},
title={Modeling Land Change using One or Two Time Points based Calibration - A Comparison of Factors},
booktitle={Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GAMOLCS,},
year={2017},
pages={341-349},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006384503410349},
isbn={978-989-758-252-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GAMOLCS,
TI - Modeling Land Change using One or Two Time Points based Calibration - A Comparison of Factors
SN - 978-989-758-252-3
AU - Camacho Olmedo M.
PY - 2017
SP - 341
EP - 349
DO - 10.5220/0006384503410349