## Results
### Mapping of Burnt Areas with Sentinel-1 and Sentinel-2  
Maps of burnt areas at a 20 and 25 m resolution are obtained from S2 and S1 images. Burnt areas from S2 are mapped on a 10-day basis, from the 12 January to the 21 May 2016. The gap in S2 images from mid-February to mid-March is compensated by a cloud free acquisition mid-March. Two maps of burnt areas are produced from S1 data, one capturing the difference between December 2015 and January 2016 and the second one for the period December 2015 to March 2016. This mapping is based on the difference of the backscatter signal during those periods of time. As illustrated in Figure 6, the maps of burnt areas derived from S1 and S2 images are not identical. The burnt area estimations by S1 and S2 are presented in Table 1. The estimations vary from around 26,000 ha for S1 to 33,000 ha for S2. Some areas are not detected by S2 because of constant high cloud coverage. Overall, S1 detects a smaller extent of burnt area than S2 due to the choice of a conservative threshold to avoid overestimation related to the change of water content in the vegetation. Figure 5: The number of active fires detected by the MODIS sensors on-board Aqua and Terra for the study area. The long term (2000–2014) average is under 50 fires per month, compared to a peak in January 2016 of over 250 fire events, of which a large proportion occurred in the Marantaceae open forests. The maps obtained from S1 and S2 present a 63% spatial coherence (Figure 6). A common area of 22,874 ha is found between S1 and S2 (Table 1). The location of active fires (MODIS) is coherent with maps of burnt areas derived from S1 and S2 imagery. The final combined S2-S1 map is presented in Figure 7. In terms of area, the combined S2-S1 map is detecting an area affected by fire of 36,247 ha in the study area for the period January-April 2016 (Table 2). Of this area, more than 32,382 ha are localized in the Ngombe logging concession. The burnt areas represent about 3% of the concession total area. Some burnt areas are also observed in the Pokala and Loundoungou Toukalaka logging concessions, situated outside the study area, but represent a much smaller spatial extent. \begin{table}
\begin{tabular}{c c c c} \hline  & \multicolumn{3}{c}{**Burnt Area (in ha)**} \\ \hline
**Sentinel 2 (S2)** & **Sentinel 1 (S1)** & **S2 and S1 Combined** & **Intersection of S2 and S1** \\
32,997 & 26,124 & 36,247 & 22,874 \\ \hline \end{tabular}
\end{table} 
Table 1: Comparison of the detection of burnt areas with Sentinel 2 and Sentinel 1 derived maps. Figure 6: Spatial coherence in the location of the burnt areas as detected by: Sentinel 2 (S2) (**A**); and Sentinel 1 (S1) (**B**) and MODIS active fire product (black dots). (**C**) Map obtained by combining S2 and S1 based maps. S2 data (27 January 2016) are in the background. In terms of forest type affected by the fires, it is crucial to notice that the fires are restricted to a very specific type of forests formation. A spatial comparison of the extent of burnt areas and the vegetation map of [PERSON] et al., [26] showed that 83% of the burnt area is localized in the core of Marantaceae forests and another 13% in the border of these forests. Another 2% is found in dense forest classes. The rest are found in a mixture of classes, probably due to the coarse spatial resolution of the vegetation map creating a geometric mismatch. In conclusion, 96% of the burnt areas are localized in very open to open forest formations. \begin{table}
\begin{tabular}{c c} \hline \hline
**Burnt Area (in ha) for the Combined S2 and S1 Map** \\ \hline Marantaceae forest & 30,128 (83.1\%) \\ Border of Marantaceae forest & 4575 (12.6\%) \\ Dense forests & 678 (1.9\%) \\ In the logging concession (Ngomble) & 32,382 (89\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Estimation of burnt area in the forest classes with the Sentinel 2 and Sentinel 1 combined product.