# NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies
## 3 Results
### Storms  
For Hurricane Maria, we used seven DNB images prior to the storm and five images after the storm (Table 6) to compute the average composite DNB images pre- and post-storm. Hurricane Maria occurred during the rainy season during very high average cloud coverage of 85.0% within the first 10 days after the hurricane. As such, we were unable to use NTL these days. Given that 84% of the island was still without power 20 days after the hurricane [50], we averaged the DNB for 20 days after the hurricane as the post-storm data. Figure 5a-c show the pre- and post-storm averaging composite DNB images and the PNL image. Most areas of the island were darker after the hurricane, with only a few exceptions. The size of the darker areas was calculated to be 9581.6 km\({}^{2}\) and the brighter areas were only 53.4 km\({}^{2}\). The DNB changes post-earthquake were statistically significant (Mann-Whitney U-test, \(p<0.001\)). Figure 5: **(a)** The pre- and **(b)** post-storm averaging composite DNB images, **(c)** PNL image, **(d)** DPM image, **(e)** OSM building map combined with PNL image, and **(f)** DPM image compared with the building map of Hurricane Maria. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Study Area** & **Number of Buildings 1** & **Total Population 2** &
\begin{tabular}{c} **Average Number of** \\ **People Per Building** \\ \end{tabular} \\ \hline Kathmandu and the & & & \\ surrounding area, Nepal & 220,451 & 3,566,322 & 16.2 \\ \hline Four counties in Italy & 12,234 & 9371 & 0.8 \\ \hline \hline \end{tabular}  
* The number of buildings was calculated from the OSM building map in the study areas. 2 The total population was extracted from the Gridded Population of the World (GPW) dataset, v4. ([[http://sedac.ciesin.columbia.edu/data/collection/gpw-v4](http://sedac.ciesin.columbia.edu/data/collection/gpw-v4)]([http://sedac.ciesin.columbia.edu/data/collection/gpw-v4](http://sedac.ciesin.columbia.edu/data/collection/gpw-v4))).  
\end{table} 
Table 5: The building numbers and population in the study areas of the two earthquake events. By comparing the PNL image (Figure 5c) with the damaged areas from DPM (Figure 5d) produced by ARIA using CSK SAR data, we found that the damaged areas in DPM were sporadic and the extent of the damaged area was lesser than that of the darker area detected by NTL. By overlaying the DPM map with the building map (Figure 5f), we calculated that only 1.6% of the total building areas were affected by Hurricane Maria. This proportion of building damage was significantly less than the proportion of darker pixels (99.4%), indicating that the building damage was not reflected by NTL in this case. This could possibly be attributed to the large-scale power outages resulting in the darkening of both damaged and non-damaged buildings, as well as areas where no buildings were present (Figure 5e). We used the power outage data from the Hurricanes Event Summary Reports published by the U.S. Office of Cybersecurity, Energy Security, and Emergency Response (CESER) to verify the use of PNL to track power outages and recovery trends [50]. These reports provide data about the percent of customers without power (P\({}_{\text{nopower}}\)) for 45 days in Puerto Rico for the period from 20 September to 6 November 2017 and from 3 January to 4 April 2018. Using a piecewise linear interpolation, we estimated the P\({}_{\text{nopower}}\) for the other days during this period except for the period from 7 November 2017 to 2 January 2018 where no data were available for this period. We composited the DNB data every 10 days after the storm (except for the period where no P\({}_{\text{nopower}}\) data were available), then selected the composite images not affected by clouds to calculate the PNL value for the whole island by dividing the mean post-storm DNB radiance by the mean pre-storm DNB radiance (Table 7). The P\({}_{\text{nopower}}\) values for the selected days were averaged and used as validation data (Table 7).