# Evaluation of Light Pollution in Global Protected Areas from 1992 to 2018
## 5 Discussion
### Uncertainty  
Here, we discussed the uncertainty of the evaluation of light pollution using the harmonized global NTL dataset [2]. The uncertainty of this dataset mainly lies in two aspects, including the employed data and model. On the one hand, the DMSP and VIIRS NTL, as two different kinds of data, have different observation records (i.e., digital number and radiation), transit time (i.e., 9:00 pm and 1:30 am), and spatial resolution (i.e., 30-arc and 15-arc). On the other hand, a sigmoid function was employed to convert VIIRS radiance  
Figure 8: The relationship between light pollution (i.e., the ratio of polluted PA with an increasing trend) and urbanization (i.e., the increasing rate of impervious surface areas).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{2}{c}{**The Polluted Protected Areas**} & \multicolumn{3}{c}{**Impervious Surface Area**} \\  & **Increasing** & **Decreasing** & **Total** & **1992 (km\({}^{2}\))** & **2018 (km\({}^{2}\))** & **Increasing** \\  & & & & & **Rate** \\ \hline Japan & 172 (12\%) & 1221 & 1404 & 19972 & 29402 & 147.21\% \\ United Sated & 1578 (28\%) & 4104 & 5702 & 162,000 & 272,000 & 167.90\% \\ \hline Africa & 416 (74\%) & 143 & 559 & 27,913 & 55,665 & 199.42\% \\ Asia & 1699 (47\%) & 1900 & 3621 & 169,000 & 474,000 & 280.47\% \\ Europe & 4364 (50\%) & 4271 & 8697 & 127,000 & 260,000 & 204.72\% \\ North American & 2262 (29\%) & 5556 & 7845 & 185,000 & 320,000 & 172.97\% \\ Oceania & 950 (45\%) & 1146 & 2115 & 7927 & 15,637 & 197.27\% \\ South American & 1111 (78\%) & 305 & 1421 & 20,622 & 51,091 & 247.75\% \\ Global & 13,786 (56\%) & 10,792 & 24,650 & 537,461 & 1,176,393 & 218.88\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistics of polluted PAs and impervious surface area across different regions.  
data to the DMSP-like data. When the DMSP-like digital number values from VIIRS are low, the uncertainly of the model is relatively large. Therefore, a technical validation was performed, and it was discovered that excluding low luminance regions using the threshold of 7, the derived NTL result from VIIRS is closer to the DMSP data [2]. Some nighttime light with DN values less than 7 in small towns and settlements might be neglected in our study. Overall, the approach in this dataset outperforms other approaches in terms of temporal consistency. For example, we compared the results with other studies on global light pollution [23]; a similar temporal trend distribution appeared (e.g., the east of the USA and Japan have a clear decline trend in NTL from the DMSP).  
There are additional limitations between satellite-based global light pollution evaluation and ground light pollution measurement. First, the outdoor lighting facilities and technologies rapidly change in the spectrum, direction, and total flux of lamps [60]. As a result, the night sky will change, and the traditional NTL observations such as DMSP/OLI and VIIRS/DNB may fail to detect new light sources such as blue light. Second, due to the viewing angle, polarization, and wavelength, the ground light pollution cannot be directly observed by satellites [38; 69]. Future satellite mega-constellations are expected to significantly increase light pollution [74], which brings great uncertainly to future research on light pollution.