## 4 Discussion and Conclusions
### Discussion
#### 4.1.3 Comparison with Existing Studies  
In this study, impervious surfaces corresponding to different landform types in topographic fragmentation areas were extracted, and the results of the study contributed to the nighttime light images. First, the extraction queues of the three data showed that the accuracy of the three images in extracting the spatial extent of impervious area initially increased and then decreased with the increase in DN threshold value. The highest extraction accuracy based on Luojia1-01 also appeared in the larger range of DN values. This indicated that the Luojia1-01 data could provide finer spatial details compared to other data sources, which was consistent with the results of a previous study [50].  
Second, comparing the extraction results obtained using Luojia1-01, NPP-VIIRS, and Flint nighttime lighting data demonstrated that the impermeable surfaces of three different types of cities extracted using the Flint data in topographic fragmentation areas showed the smallest error. However, the high spatial resolution of the Luojia1-01 image rendered it more sensitive to environmental changes compared with the lower resolution NPP-VIIRS and Flint images. Consequently, the impervious surface extraction from the Luojia1-01 data in topographically flat areas showed more errors in terms of omission and biased extraction results. On the other hand, the area of impervious surface extracted in topographically broken areas was larger than the actual impervious surface area. However, remote urban cores could be identified better using the Luojia1-01 data. In contrast, the impermeable surface extracted using the NPP-VIIRS data was more complete, which was consistent with the findings presented in [45].  
Third, unlike the findings of previous studies, nighttime light imagery of topographically fragmented areas was less affected by light spillover and oversaturation effects, possibly due to cloudy conditions, monitoring time, etc. The only exception to this behavior was exhibited by Flint images. This behavior was inconsistent with our initial hypothesis that the spillover effects would be severe for nighttime light imagery of topographically fragmented areas. In previous studies that compared the application of different nighttime light imagery data sources, a few experts considered the Flint nighttime light data that could smooth out surface factors. However, in this study the impermeable surface extracted from the Flint nighttime light data was heavily influenced by over-saturation and had poor accuracy. This dataset needs to be further explored in subsequent studies to explore its potential applications.  
Fourth, this study found that the impervious surface density extracted at different resolutions in the topographically flat and contiguous area was less affected by the resolution. At the same time, the extraction results from the three datasets tended to be consistent in spatial distribution in terms of high-density impervious surface distribution and formed a high-density impervious surface aggregation area centered on the central city. This is an area that has not been considered in previous studies, and the correlation between impervious surface density and topography should be analyzed further to provide theoretical support for the application of nighttime lighting.  
Fifth, the mutation detection method used in this study extracts impermeable surfaces. In the process of extracting impermeable surfaces of Karst canyons using NPP-VIIRS data, the queue value 88 was selected as the queue point; however, a small increase in perimeter occurred after DN = 91. We reviewed the relevant literature and did not find any explanation for this phenomenon. We hypothesize that the specific reason may be due to the fragmentation of Karst canyon topography, which causes two peaks in the extraction process. This may be a novel finding in this paper, and a more detailed analysis of this finding is needed in subsequent studies.