## 4 Results and Accuracy Assessment
### Accuracy Assessment  
To evaluate the impact of time-series InSAR deformation data on the accuracy of the hazard assessment results, this study uses the ablation experiment method to compare the risk level assessment results of two models, with and without the inclusion of time-series InSAR deformation data as evaluation factors. The accuracy of the results is validated using the ROC (Receiver Operating Characteristic) curve [37]. The ROC curve is a tool used to assess the performance of classification models by calculating the AUC (Area Under the Curve) value, which is used to evaluate the accuracy of the model's zoning results [38]. The AUC value is used to assess model accuracy, with an AUC between 0.5 and 0.7 indicating poor accuracy, an AUC between 0.7 and 0.9 indicating good accuracy, and an AUC above 0.9 indicating excellent accuracy. The closer the AUC value is to 1, the higher the model's precision.  
The experimental results are shown in Figure 6. The horizontal axis of the ROC curve represents the cumulative percentage of area, ranked from high to low information value, while the vertical axis represents the cumulative percentage of geological disaster points within the corresponding information value range. The AUC values obtained from the Information Value model before and after incorporating the time-series InSAR deformation results were 0.846 and 0.928, respectively. For the Evidence Weight model, the AUC values before and after including the time-series InSAR deformation results were 0.826 and 0.919, respectively. The results show the following: (1) After incorporating the time-series InSAR deformation results into the models, the accuracy of the hazard assessment results increased by 9.69% and 11.26% for the two evaluation models, respectively. This indicates that integrating time-series InSAR deformation data into the evaluation models can enhance the accuracy of hazard assessment; (2) There are differences in hazard zoning between the evaluation models. According to the hazard zoning results for Xiaojin County in this study, the Information Value model achieved higher accuracy than the Evidence Weight model, with the performance further improving after incorporating the InSAR monitoring results.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Hazard Level** & \begin{tabular}{c} **Area Ratio** \\ **(IVM)** \\ \end{tabular} & \begin{tabular}{c} **Area Ratio** \\ **(EWM)** \\ \end{tabular} & \begin{tabular}{c} **NEGHP** \\ **(IVM)** \\ \end{tabular} & \begin{tabular}{c} **NEGHP** \\ **(EWM)** \\ \end{tabular} & \begin{tabular}{c} **PEGHP** \\ **(IVM)** \\ \end{tabular} & \begin{tabular}{c} **PEGHP** \\ **(EWM)** \\ \end{tabular} & \
\begin{tabular}{c} **NEGHPA** \\ **(IVM)** \\ \end{tabular} &
\begin{tabular}{c} **NEGHPA** \\ **(EWM)** \\ \end{tabular} \\ \hline Low hazardous area & 27.28\% & 50.93\% & 1 & 4 & 0.66\% & 2.63\% & 0.0007 & 0.0014 \\ Medium hazardous & 43.14\% & 33.18\% & 13 & 18 & 8.55\% & 11.84\% & 0.0055 & 0.0099 \\ High hazardous area & 19.36\% & 9.04\% & 27 & 40 & 17.76\% & 26.32\% & 0.0255 & 0.0809 \\ Extremely hazardous area & 10.22\% & 6.85\% & 111 & 90 & 73.03\% & 59.21\% & 0.1986 & 0.2403 \\ \hline \hline \end{tabular}  
* NEGHP: Number of existing geological disaster points; PEGHP: Proportion of existing geological disaster points; IVM: Information Volume Model; EWM: Evidence Weight Model; NEGHPA: Number of existing geological disaster points per unit area.  
\end{table}
Table 3: Comparison between the results of hazard assessment and the distribution of existing geological disasters.