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4. Model Prediction

This documentation will show how to use the coefficient set acquired through calibration to initialize future land cover change in a region. However, SLEUTH will execute in predict mode with any set of coefficients with values between 0 - 100 (not necessarily derived through calibration.)

4.1 Set constants

4.1.1. Update input data

This step is optional. SLEUTH maybe used to run alternative scenarios of regional growth by altering the input data used to initialize multiple prediction runs. Otherwise, the same input used for calibration maybe used. For more information on generating alternative scenarios click here.

4.1.2. Modify scenario file for prediction*

  1. Create a copy of, or modify the scenario file used to derive forecasting coefficients, or modify the scenario.demo200_predict file contained in the downloaded Scenarios directory.
    New filename example: scenario.mydata_predict
  2. Edit INPUT_DIR flag to point to the directory of your full resolution images
  3. Edit OUTPUT_DIR flag to point to a desired output directory
  4. Set Output file flags to "YES" in order to create desired statistic files (at least avg.log is recommended)
  5. The NUM_WORKING_GRIDS flag might have to be increased. If the setting is too low an error message will be printed to the screen upon execution.
  6. Set the MONTE_CARLO_ITERATIONS flag to a high number (100 or greater)
  7. Set coefficient settings for prediction
    Enter the coefficient set derived from calibration into the PREDICTION_*_BEST_FIT flags, where (*) represents each coefficient type.
  8. Set prediction date range
  9. Edit input image flags to represent your desired files for this prediction scenario
  10. Alter colortable values if desired

* These are recommended modifications for an average prediction run. Other output specifications are available in the scenario file. The user is encouraged to review the scenario file thoroughly in order to select and implement these utilities.

4.2. Run a prediction

  1. Execute a calibration run
    prompt% ../grow predict scenario.mydata_predict
  2. Monitor progress
    If ECHO flag is set to "YES" growth years should be printed to the screen as the model executes.

4.3. Examine Output