AUC is used for validating a landslide susceptibility map. How can we prepare a AUC curve using SPSS software to assess validity of landslide susceptibility model?
Suhel Sen
AUC stands for Area Under the Curve, which is a widely used metric for evaluating the performance of classification models.
Here are the steps to prepare an AUC curve in SPSS for landslide susceptibility modelling:
I hope this helps you prepare an AUC curve in SPSS for landslide susceptibility modelling
To prepare an AUC curve using SPSS software to assess the validity of a landslide susceptibility model, follow these steps:
1. Open SPSS software and import your dataset containing the predicted probabilities of landslide occurrence and the actual occurrence of landslides.
2. Click on the “Analyze” menu and select “ROC Curve.”
3. In the “ROC Curve” dialog box, select the variable containing the predicted probabilities as the “Test Variable.”
4. Select the variable containing the actual occurrence of landslides as the “State Variable.”
5. Click on the “Options” button to specify additional options for the AUC curve. Here, you can choose to display the AUC value, confidence intervals, and other statistics.
6. Click “OK” to generate the AUC curve.
7. The AUC curve will be displayed in a new window. You can customize the graph by adding labels, changing colors, and adjusting the axis scales.
8. Analyze the AUC curve to evaluate the performance of your landslide susceptibility model. The AUC value ranges from 0 to 1, with higher values indicating better model performance. A value of 0.5 indicates that the model is no better than random chance.
9. Interpret the AUC curve in conjunction with other performance metrics, such as sensitivity, specificity, and accuracy, to assess the validity of your landslide susceptibility model.
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