## 1 Introduction  
Satellite data have been used to systematically monitor fire globally at coarse spatial resolution, using algorithms that detect the location of active fires at the time of satellite overpass, and using burned area mapping algorithms that map the spatial extent of the areas affected by fires [1; 2; 3; 4; 5; 6; 7]. There is a need for moderate spatial resolution burned area products at regional to global scale that to date has only been partially met [8]. The launch of Sentinel-2A and the forthcoming launch of the Sentinel-2B satellite that carry the Multi Spectral Instrument (MSI) [9] provide the opportunity for moderate spatial resolution burned area mapping. Combined, the Sentinel-2A and -2B systems will provide multi-spectral global coverage up to every 5 days. The MSI has 13 spectral bands ranging from 0.433 um to 2.19 um; four 10 m visible and near-infrared bands, six 20 m red edge, near-infrared (NIR) and short wave infrared (SWIR) bands, and three 60 m bands for characterizing aerosols, water vapor and cirrus clouds [9]. The MSI bands are similar to the Landsat-8, SPOT-6 and SPOT-7 bands and so include wavelengths that are suitable for burned area discrimination. Burned areas are characterized by deposits of charcoal and ash, and also by the removal of vegetation and alteration of the vegetation structure that sometimes reveal the vegetation understory and/or soil [10; 11; 12]. The fire behavior controls the severity of fire effects including the degree and parts of the vegetation structure that burned, the amount of charcoal and ash deposition, the combustion completeness, and the size and spatial distribution of the burning [13; 14]. The persistence of the charcoal and ash signal depends on rates of dissipation by wind and rain and may be controlled by the unburned fuel load and structure [15; 16]. Post-fire the vegetation may regrow, at rates dependent on the site primary productivity and environmental factors and have a phenological signal that complicates burned area detection [17; 18; 19; 20]. Consequently, the reflectance over a burned area may have considerable variation in space and time as the spectral characteristics of unburned and burned areas change. In general, NIR and shortwave-infrared wavelengths have been found to provide stronger burned area discrimination than visible wavelengths, and most burned area mapping algorithms are based on detecting decreased reflectance at these wavelengths. However, in some cases reflectance can increase due to the exposure of highly reflective soil and white ash deposition [12; 21; 22]. In addition, some surface changes not associated with fire, such as shadows or agricultural harvesting, may induce similar spectral changes and depending on the algorithm and wavelengths used may cause false burned area detection [2; 23]. Visible wavelengths are not generally suitable for burned area detection because they are more sensitive to atmospheric contamination than longer wavelength bands and in particular are sensitive to smoke aerosols that are difficult to atmospherically correct [24; 25]. A large number of researchers have used spectral indices to map burned areas. Ideally, if a spectral index is appropriate to detect the physical change of interest, then there is a simple relationship between the change and the direction of the change displacement in spectral feature space [26]. However, burned area spectral indices have often been designed quite empirically, for example, by considering every possible combination of bands and a variety of non-linear band transformations [27; 28; 29; 30; 31]. Although spectral indices may produce good burned area discrimination for a particular location and time they may not perform well elsewhere. Commonly, indices based on spectral band ratios, usually of NIR and SWIR wavelengths that are less sensitive to atmospheric contamination, are used. The ratio formulation reduces first order bi-directional reflectance and solar zenith induced reflectance variations [32].