# On the Potential of the RST-FLARE Algorithm for Gas Flaring Characterization from Space
## 4 Validation Analyses
### Flaring Sites  
The temporal and spatial distribution of flaring sites, discussed in Section 3.1, were validated using two independent datasets (see Section 2.2).  
About the first analysis, the flaring sites annually detected by RST-FLARE, in terms of temporal trend (solid line in Figure 5) and number, for onshore and offshore as well as for each state (Table 1), were compared with results achieved by [12].  
By qualitatively comparing the temporal trend of flaring sites detected by the MODET algorithm (dashed black line in Figure 10, qualitatively extracted from Figure 7 in [12]) in the Niger Delta from 2000 to 2014 with the ones obtained by RST-FLARE (solid black line in Figure 10), a correlation of 74% was found.  
Observing Figure 10, it is interesting to note that both algorithms show a general decreasing trend in the number of flaring sites during the whole investigated period, with a rate slightly higher for RST-FLARE than MODET. Although some discrepancies between the two series are evident, the two products are quite similar, not only in the temporal trend but also in terms of the order of magnitude of the annual detected flares.  
Besides, a quantitative comparison between the spatial distributions of flaring sites detected onshore and offshore by RST-FLARE (Table 1) and MODET (Table 4 in [12]) was carried out. These algorithms identified a very similar distribution of flaring sites between onshore (68% for  
Figure 9: Plots of the linear regression models generated by exploiting (**a**) OPEC and (**b**) EIA dataset.  
RST-FLARE, 70% for MODET) and offshore (32% for RST-FLARE, 30% for MODET) zones. In addition, when the flaring sites distribution across the seven Niger Delta States is compared (see values in Table 3), the agreement of the two algorithms grouped up to 99% for onshore detections and 88% for the offshore ones (Table 3).  
To better validate the spatial distribution of the detected flaring sites, a fully independent satellite-based map, the VNF product [7], was also used. It is worth underlining that RST-FLARE and VNF, although based on a different multi-temporal aggregation scheme for the gas flares detection (17 years long for RST-FLARE and 5 for VNF, aggregated on an annual and monthly scale, respectively), show significant differences, using different satellite data offering different spatial, spectral and temporal resolutions. To take into account such aspects, the inter-comparison was carried out defining a 1 km - buffer zone around each detection of both VNF and RST-FLARE. In Figure 11 the spatial distribution of flaring sites detected by RST-FLARE (314 pixels, black dots in the map) and VNF (205, red crosses, extracted from the SkyTruth map) is shown. In this figure, the yellow circles highlight those flaring sites identified by both algorithms within the 1 km buffer zone.  
About 95% of the indicated flares have been commonly detected by the two algorithms, confirming their good agreement, in spite of the above mentioned significant differences between them.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**State**} & \multicolumn{2}{c}{**Onshore**} & \multicolumn{2}{c}{**Offshore**} \\ \cline{2-5}  & **RST-FLARE** & **MODET** & **RST-FLARE** & **MODET** \\ \hline
1. Edo & 19 & 19 & 0 & 0 \\
2. Delta & 56 & 51 & 23 & 19 \\
3. Bayelsa & 54 & 41 & 15 & 12 \\
4. Imo & 12 & 11 & 0 & 0 \\
5. Rivers & 70 & 56 & 34 & 16 \\
6. Abia & 1 & 1 & 0 & 0 \\
7. Akwa & 3 & 6 & 27 & 30 \\ Ibom & **Total** & **215** & **185** & **99** & **77** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Distribution of flaring sites detected, onshore and offshore, by RST-FLARE and MODET (source: Table 4 in [12]) across the seven Niger Delta states.  
Figure 10: Annual number of flaring sites detected in the Niger Delta region by RST-FLARE (solid black line) and MODET (dashed black line, adapted from [12]).