# A Spatial Reconstruction Method of Ionospheric foF2 Based on High Accuracy Surface Modeling Theory
## 4 Discussion
### Comparison between the Kriging Method and HAS Method
Therefore, the prediction effects of both methods varied with the solar activity level, and the prediction RRMSEs became smaller when the solar activity improved in the middle solar activity period relative to the low solar activity period, while the prediction RRMSE became larger in the high solar activity period relative to the middle solar activity period. This shows the important influence of solar activity on the foF2 from this side. 2. The RRMSEs of the predictions using the two methods during the four seasons are given in Figure 8b. In spring, the HAS method predicted better results than the Kriging method, with a difference of 10.83% in the RRMSEs. In summer, the Kriging and HAS methods achieved the worst predictions. In autumn, the Kriging method reached the best prediction, but the prediction was still poor compared with that of the HAS method. In winter, the HAS method predicted the best results, with an RRMSE of 8.09%. Overall, the HAS method predicted better results than the Kriging method under all four seasons. 3. The RRMSEs of both methods during the day and at night are shown in Figure 8c. The prediction RRMSE of the Kriging method decreased by 7.66% during the daytime compared with nighttime, and the prediction RRMSE of the HAS method increased by 1.94% during the nighttime compared with daytime. Overall, the HAS method's predictions were better than the Kriging method both during the day and at night, and both method's predictions were better during the day. 4. Overall, the HAS method outperformed the Kriging method in different seasons, solar activity levels, and at daytime and nighttime. This confirms the effectiveness and precision of the HAS method introduced in this paper and provides a new approach and methodology for the prediction of ionospheric parameters. To present the reconstruction outcomes of both methods in a more intuitive manner, Figure 9 shows the results of spatial reconstruction using the HAS method and the Kriging method at different times:  
1. The reconstruction outcomes of the HAS and Kriging methods at 12:00 p.m. local time for the high solar activity year in November 2014 are illustrated in Figure 9a,b, respectively. The figures show that the value domains reconstructed by the HAS method ranged from 7.5 to 12, and the value domains reconstructed by the Kriging method ranged from 7.5 to 11.5, indicating that the values reconstructed by the HAS method would be larger than those reconstructed by the Kriging method in some regions. In addition, the results of the reconstruction by the HAS method can be observed as multiple obvious contour circles, which represent the large value variations of the local regions, with obvious high-value areas. In contrast, the contour lines in the reconstructed results of the Kriging method are relatively smooth, and there is no obvious local variation in the HAS method. 2. Figure 9e,f shows the distribution of the RRMSEs of the HAS and Kriging methods in predicting the seven stations at 12:00 p.m. local time for the high solar activity year in November 2014, respectively, and the RRMSE plots of the HAS method show that the RRMSEs were larger at some points in the plots but smaller at most stations. Compared with the prediction of the RRMSEs for the Kriging method, the HAS method predicted the RRMSEs of all seven stations better than the Kriging method. 3. The reconstruction outcomes of the HAS and Kriging methods at 12:00 a.m. local time for the low solar activity year in July 2018 are illustrated in Figure 9c,d, respectively. The figure shows that the local area reconstructed by the HAS method had a large change in value. For example, an obvious high-value area can be seen in the upper right of the figure. The transition between the high-value and low-value areas in the reconstructed results of the Kriging method is relatively smooth, and the characteristics of the spatial distribution are not as obvious as those of the HAS method, which lacks some details. 4.