Can I change the time step interval when predicting future urban growth with a cellular automata model?

Conditions

• The model has been calibrated using historical data.
• The user defines the prediction time step.

Reasoning, step by step

1. Identify the historical data interval used for calibration (e.g., 5 years).
2. Recognize that this interval is not a strict requirement for future prediction.
3. Set the desired prediction time step (e.g., 10 or 15 years) based on analytical needs.
4. Apply the calibrated model to the latest base map to project future scenarios.

Example

The speaker clarifies: 'I have taken five years, that's not necessary. So you can directly take 10 years, 15 years based on your requirement.' Once the model is trained, the 2014 land cover map is used to predict for future.

Common misconceptions

• Believing that the cellular automata model must strictly use the same time interval (e.g., 5 years) as the historical training data for future predictions. The time step for prediction is flexible.

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