Integrating Temporal Evolution with Cellular Automata for Simulating Land Cover Change

  title={Integrating Temporal Evolution with Cellular Automata for Simulating Land Cover Change},
  author={Cangjiao Wang and Shaogang Lei and Andrew J. Elmore and Duo Jia and Shouguo Mu},
  journal={Remote Sensing},
Simultaneously considering the spatial and temporal processes is essential for land cover simulation models. A cellular automaton (CA) usually simulates the spatial conversion of land cover through post-classification comparisons between the beginning and the end of the training period. However, such an approach does not consider the temporal evolution of land cover. As a result, a CA model fails to explain the realistic land cover change. This paper proposes a temporal-dimension-extension CA… CONTINUE READING

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Key Quantitative Results

  • Furthermore, the overall accuracy and the Kappa coefficient of the TDE-CA were 79.84% and 71.61%, respectively; compared with the TESM and the optimized RF-CA, the values showed 17.14% and 4.48% improvements in the overall accuracies and 0.2167 and 0.0512 improvements in the Kappa coefficients, respectively.


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