## 4 Discussion
### Potential of Sentinel 1 and Sentinel 2 for Burnt Areas Monitoring  
To monitor and map fire events in tropical forests, the sensors installed on the S1 and S2 satellites show some potential. The arrival of the S2 satellite provides a far higher frequency of Earth Observation data than was previously possible at this fine (10-20 m) spatial resolution. Due to its novelty, literature about the use of time series of S2 images is scarce and mainly covers the use of single or pair of images but first experiences confirm a good potential for land cover mapping capabilities [59; 60]. The frequent observations by S1 over the Congo Basin and its independence from cloud cover also make the mission an indispensable asset. The use of the two sensors (supported by the active fires from MODIS) allows a fuller picture of what has actually occurred.  
Figure 9: (**A**) Percentage of tree cover derived from a 2011 GeoEye image; (**B**) Burnt areas in 2016 detected on Sentinel images; (**C**) Zoomed in GeoEye image showing the transition from very open canopy to open forest canopy; and (**D**) Timing of the detection of burnt area for the magnified image. Fire happened first in the more open areas.  
The two sensors are sensitive to different phenomena, the S2 optical sensor detecting changes in surface reflectance, while the S1 SAR is detecting changes in vegetation structure and moisture. It may therefore be that the S1 SAR is only highlighting areas where the fires were more intense, and the vegetation structure was more affected, which can only be assessed with field data.  
With S1 data, some technical constrains have to be respected. In order to remove speckle and noise, monthly composites have to be used. Due to the high rainfall in November and the drought of December to February, the change of soil moisture had an impact on the changes in backscattering, requiring a higher threshold for the detection of burnt areas. Some small errors of commission were observed most probably due to the change in soil moisture. Errors due to the topography are not expected here, as the study area is quite flat.  
With S2 optical data, cloud cover limits the data available and unlike other regions the dry season in Africa does not mean an absence of clouds [25]. However, changes in reflectance can be captured for a few months, depending on the pace of vegetation regrowth.  
The limitations of the individual systems are reduced by using both S1 and S2. Figure 10 illustrates the extreme cases for each sensor. In Figure 10A, S2 detects burnt areas (in blue) while S1 does not, probably because of a less severe fire. In Figure 10B, however, S1 (in orange) detects burnt areas that were not detected by S2 due to high cloud coverage.  
Clearly, the combination of the Sentinel data with that of Landsat would further improve the temporal coverage.  
Figure 10: Examples of complementary use of Sentinel 1 and Sentinel 2 data in two specific zones of the study area (**A**) and (**B**). Areas detected only by Sentinel 2 are in blue, only by Sentinel 1 in orange and areas detected as burnt by both sensors are in dark red. Active fires (MODIS) are represented by the black dots.