Calibrating nonparametric cellular automata with a generalized additive model to simulate dynamic urban growth

@article{Feng2017CalibratingNC,
  title={Calibrating nonparametric cellular automata with a generalized additive model to simulate dynamic urban growth},
  author={Yongjiu Feng and Xiaohua Tong},
  journal={Environmental Earth Sciences},
  year={2017},
  volume={76},
  pages={1-15}
}
Understanding factors that drive urban growth is essential to cellular automata (CA) based urban modeling. Multicollinearity among correlated factors may cause negative effects when building CA transition rules, leading to a decrease in simulation accuracy. We use a nonparametric generalized additive model (GAM) to evaluate these relationships through flexible smooth functions to capture the dynamics of urban growth. A GAM-based CA (termed GAM-CA) model was then developed to simulate the rapid… CONTINUE READING
1
Twitter Mention

Figures and Tables from this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 76 REFERENCES

A neighbor decay cellular automata approach for simulating urban expansion based on particle swarm intelligence

  • International Journal of Geographical Information Science
  • 2014
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Simulating urban growth by integrating landscape expansion index (LEI) and cellular automata

  • International Journal of Geographical Information Science
  • 2014
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Calibration of stochastic cellular automata: the application to rural-urban land conversions

  • International Journal of Geographical Information Science
  • 2002
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL