Skip to main content
SpringerLink
Log in

Scenario simulation and forecast of land use/cover in northern China

  • Articles
  • Geography
  • Published:
Chinese Science Bulletin

Abstract

Modeling land use/cover scenario changes and its potential impacts on structure and functions of ecosystem in typical regions are helpful to understanding the interactive mechanism between land use/cover system and ecosystem. Based on the analysis of the existing land use/cover simulation and forecast models, a land use/cover scenario dynamics model by the integration of System Dynamics (SD) model, Back Propagation Neural Network (BPNN) and Cellular Automata (CA) model is developed with land use/cover scenario changes in northern China in the next 30 years and simulated in this paper. The model is to simulate the land use/cover scenario demands by using a SD model at first, and then allocating the land use scenario patterns at the local scale with the considerations of land use/cover suitability, inheritance ability and neighborhood effect by using BPNN-CA model to satisfy the balance between land use/cover scenario demands and supplies. It integrates the advantages of SD, BPNN and CA. Macro-driving factors and the micro-spatial pattern are also fully taken into account. The BPNN simplifies the identification of the factors’ weights used in CA model and improves the reliability of the simulation results. The simulation accuracy of the model developed in this paper was found to be about 74%. It suggests that the model has the ability to reflect the complexity of land use/cover system at different scales to some extent and it is a useful tool for assessing the potential impacts of land use system on ecosystem. The simulated results also indicate that the urban land, water area and forest will increase significantly, and farmland and unable land will decrease gradually. Obvious land use/cover changes will take place in the farming-pastoral zone and the southeast area of northern China.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Dawn C P, Steven M M, Marco A J, et al. Multi-Agent systems for the simulation of land-use and land-cover change: A review. Ann Assoc Am Geogr, 2002, 8: 93–100

    Google Scholar 

  2. Pijanowski B C, Brown D G, Manik G, et al. Using neural nets and GIS to forecast land use changes: A land transformation model. Computers. Environ Urban Syst, 2002, 26(6): 553–575

    Article  Google Scholar 

  3. Bai W Q, Zhao S D. A comprehensive description of the models of land use and land cover change study. J Nat Resour (in Chinese), 1997, 12(2): 169–175

    Google Scholar 

  4. Veldkamp A, Fresco L O. CLUE: A conceptual model to study the conversion of land use and its effects. Ecol Model, 1996, 85: 253–270

    Article  Google Scholar 

  5. He C Y, Chen J, Shi P J, et al. City expansion model of metropolitan area in China: a case study of Beijing. Acta Geogr Sinica (in Chinese), 2003, 58(2): 294–304

    Google Scholar 

  6. He C Y, Shi P J, Chen J, et al. Land use scene model based on system dynamics model and CA model. Sci China Ser D-Earth Sci (in Chinese), 2005, 35(5): 464–473

    Google Scholar 

  7. Xiong L Y, Chang B, Zhou X G. A GeoCA-based study on land use change. Resour Sci (in Chinese), 2005, 27(4): 38–43

    Google Scholar 

  8. Verda K, Suzana D. Coupling Bayesian networks with GIS-based cellular automata for modeling land use change. Lect Notes Comput Sc, 2006, 4197: 217–233

    Google Scholar 

  9. Lambin E F, Turner B L, Geist H J, et al. The causes of land use and land cover change: moving beyond the myths. Global Environ Change, 2001, 11: 261–269

    Article  Google Scholar 

  10. Lambin E F, Rounsevell M D A, Geist H J. Are agricultural land-use models able to predict changes in land-use intensity?. Agric, Ecosyst Environ, 2000, 82: 321–331

    Article  Google Scholar 

  11. Li Y C. Study on land use/cover change in northern China. Dissertation for Doctoral Degree (in Chinese). Beijing: Beijing Normal University, 2006. 94–97

    Google Scholar 

  12. Zhang H, Zhang B. Review on land use and land cover change models. J Nat Resour (in Chinese), 2005, 20(3): 422–431

    Google Scholar 

  13. Zhou C H, Sun Z L, Xie Y C. Geographical Cellular Automata Study (in Chinese). Beijing: Science Press, 1999. 78–103

    Google Scholar 

  14. Zhang H X. A simulation of the dynamics of soil erosion in the loess hills of Shanxi and Shaanxi provinces. Chin Sci Bull (in Chinese), 1997, 42(7): 743–746

    Google Scholar 

  15. Su M K. Theory and Application of System Dynamics (in Chinese). Shanghai: Shanghai Jiao Tong University Press, 1988. 86–98

    Google Scholar 

  16. Shi P J, Song C Q, Jing G F. Strengthening the study of land use/cover change and its impact on eco-environment security. Advan Earth Sci (in Chinese), 2002, 17(2): 161–168

    Google Scholar 

  17. Zhang Y M, Zhao S D, Verburg P H. CLUE-S and its application for simulating temporal and spatial change of land use in Naiman Banner. J Nat Resour (in Chinese), 2003, 18(3): 310–318

    Google Scholar 

  18. He C Y, Shi P J, Li J G, et al. Scenarios simulation land use change in the northern China by system dynamic model. Acta Geogr Sinica (in Chinese), 2004, 59(4): 599–607

    Google Scholar 

  19. Couclelis H. From cellular automaton to urban models: new principles for model development and implementation. Environ Plann B, 1997, 24: 165–174

    Article  Google Scholar 

  20. Zhao Y I, Yu J M. A new method to model neighborhood interaction in cellular automata-based urban geosimulation. Lect Notes Comput Sc, 2007, 4488: 550–557

    Article  Google Scholar 

  21. Li X, Yeh G O. Neural-network-based cellular automata for realistic and idealized urban simulation. Acta Geogr Sin (in Chinese), 2002, 57(2): 159–166

    Google Scholar 

  22. Batty M, Xie Y, Sun Z. Modeling urban dynamics through GIS-based cellular automata. Computer Environ Urban Syst, 1999, 23: 1–29

    Article  Google Scholar 

  23. Li X, Liu X P. An extended cellular automaton using case-based reasoning for simulating urban. Int J Geogr Int Sci, 2006, 20(10): 1109–1136

    Article  Google Scholar 

  24. Wu F, Webster C J. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environ Plann B, 1998, 25: 103–126

    Article  Google Scholar 

  25. Li X, Yeh G O. Knowledge discovery for geographical cellular automata. Sci Chin Ser D-Earth Sci, 2005, 48(10): 1758–1767

    Article  Google Scholar 

  26. Liu X P, Li X. Retrieving CA nonlinear transition rule from high-dimensional feature space. Acta Geogr Sinica (in Chinese), 2006, 61(6): 663–672

    Google Scholar 

  27. Li X, Yeh A G O. Data mining of cellular automata’s transition rules. Int J Geogr Inf Sci, 2004, 18(8): 723–744

    Article  Google Scholar 

  28. Liu X P, Li X, Yeh A G O, et al. Discovery of transition rules for geographical cellular automata by using ant colony optimization. Sci China Ser D-Earth Sci (in Chinese), 2007, 37(6): 824–834

    Google Scholar 

  29. White H. Commentionist nonparametric regression: Multilayer feed forward networks can learn arbitrary mapping. Neural Networks, 1990, (3): 47–51

  30. Yang J G. Artificial Neural Network Tutorial (in Chinese). Hangzhou: Zhejiang University Press, 2001. 56–72

    Google Scholar 

  31. Zhang L M. Artificial neural Network Model and Its Application (in Chinese). Shanghai: Fudan University Press, 1993. 36–48

    Google Scholar 

  32. Li Y C, Gong P, Chen J, et al. Landscape pattern and its dynamical change in north China during 1989–1999. J Soil Water Conserv (in Chinese), 2005, 19(5): 143–146

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Geographical Science, Chongqing Normal University, Chongqing, 400047, China

    YueChen Li

  2. College of Resources and Environmental Science, Chongqing University, Chongqing, 400044, China

    YueChen Li

  3. College of Resources Science & Technology, Beijing Normal University, Beijing, 100875, China

    YueChen Li & ChunYang He

Authors
  1. YueChen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. ChunYang He
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to YueChen Li.

Additional information

Supported by the Science & Technology Research Project of Chongqing Municipal Education Commission (Grant No. KJ070811), the Doctor Startup Fund of Chongqing Normal University (Grant No. 06XLB004) and the National Key Project for Basic Sciences of China (Grant No. 2006CB400505)

About this article

Cite this article

Li, Y., He, C. Scenario simulation and forecast of land use/cover in northern China. Chin. Sci. Bull. 53, 1401–1412 (2008). https://doi.org/10.1007/s11434-008-0169-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11434-008-0169-9

Keywords

Search

Navigation