## 4 Discussion
### Comparison of PP with Permafrost Temperature (PT) and Permafrost Continuity (PC)  
Compared with the existing PT dataset [54; 75] and PC dataset [55] in the study area, the greatest advantage and improvement of this study is that the spatial resolution is increased to 30 m. Due to the improvement in spatial resolution, the dataset is applicable to the engineering field and meets the requirements of engineering reference data. However, it is impractical to achieve the mapping goal of the presence or absence of permafrost  
Figure 7: Numerical distribution of the characteristic variables in the samples with permafrost and the samples without permafrost.  
in such a resolution [16]. In high-resolution permafrost mapping, it is more feasible to take the probability of permafrost occurrence as the result than to provide the location of permafrost.  
Under the environmental background of permafrost degradation, a lower PT and higher PC should lead to a higher PP; from another perspective, a higher PT and lower PC should lead to a lower PP. Compared with the existing PT datasets and PC datasets, although the PP datasets provided in this study have different description angles and a higher resolution for permafrost, the spatial distribution law is consistent with the speculation (Figure 8).  
The PP data, PT data, and PC data in the study area were compared (Figure 9). It can be seen that the three data have similar distribution patterns of permafrost in Arvan, that is, the permafrost is mainly distributed in the GKM from the northeast to the southwest, followed by the low-altitude area in the northwest. This is closely related to the geographical and climatic conditions of the region. The GKM generally runs from northeast to southwest, blocking the Mongolian High from entering the Northeast China Plain [76], making the northwest of the GKM colder than the southeast. The research area is located in a high-latitude area of the northern hemisphere, and the solar radiation received by the surface is higher in the south than in the north. All these are the reasons why there is more permafrost in the northwest of the study area than in the southeast.  
The area with PP > 0.5 is similar in spatial distribution to the area with PT \(\leq\) 0 \({}^{\circ}\)C and PC > 10% (Figure 9a-c). The coincidence rate between the area with PP > 0.5 and the latter two is 89.9% and 97.3% respectively. The above three ranges exclude the southeast and the small urban areas in the northwest of the study area. The spatial location of the area described as a high-level permafrost area by the three datasets is close. The area with PP > 0.8 has a coincidence rate of 73.3% with the area with PT \(\leq\) -3 \({}^{\circ}\)C and a coincidence rate of 47.6% with the area with PC > 50%. This means that the spatial distribution of the three permafrost datasets has a high degree of coincidence in the whole study area. In the evaluation of the high-level permafrost area, the results of the three permafrost datasets are similar.  
Due to the improvement in high resolution, the permafrost probability data at 30 m show its strengths in distinguishing lakes, and the description of the burned area is more detailed (Figure 9d). The lakes located in cold regions have a long ice cover period and less radiation energy, which leads to the error of the remote sensing method for permafrost mapping (Figure 9(d4)). This kind of error is reduced in MaxEnt. In some areas, different data results have similar boundaries (Figure 9e). On the one hand, it confirms the applicability of the data; on the other hand, it is also valuable for the study of regional permafrost boundaries.  
Figure 8: Scatter diagram between PT and PP (**a**), PC and PP (**b**), PT and PC (**c**) in Arvan.