## Materials and Methods
### Burned Area Mapping Method
#### 2.3.3 Spectral Characteristics Analysis  
The spectral characteristics analysis consists of two parts: Spectral bands analysis and spectral indices analysis to distinguish between the burned area and unburned types. The separability index M [22; 24; 25; 31] can assess the separability between the two types, so we utilized it to analyze the capacity of the spectral band and spectral index to distinguish the burned area from unburned types. Any M value greater than 1.0 represents a superior separation between the burned and unburned type, while an M value lower than 1.0 indicates an inferior separation. The formula of separability index M is defined as follows:  
\[\mathrm{M}=(\big{|}\mu_{i,b}-\mu_{i,u}\big{|})/(\sigma_{i,b}+\sigma_{i,u}) \tag{3}\]  
where \(\mu_{i,b}\) and \(\mu_{i,u}\) are the mean value of burned pixels and unburned pixels respectively, and \(\sigma_{i,b}\) and \(\sigma_{i,u}\) are the standard deviations of burned pixels and unburned pixels respectively.  
The spectral bands of the MODIS sensor range from the visible region to thermal infrared (TIR) region. It has been demonstrated that the near-infrared (NIR) and shortwave infrared (SWIR) region are important for burned area detection [22], so we investigated the capacity of the reflectance of MODIS bands 1-7 including the visible (band 1, 3, 4), NIR (band 2, 5) and SWIR (band 6, 7) spectral regions to discriminate the burned area from unburned types. In addition, the reflectance data that is sensitive to the burned area, as well as the emissivity and LST data, which has been proved to show high separating capacity for the burned area [22; 34], were combined into the spectral indices listed in Table 4. We carried out the separability analysis of 13 spectral indices for discriminating the burned area. The spectral indices BAI, CSI, MIRBI, and NBR (burned area indices) were developed to reflect the spectral characteristics of burned land. The spectral indices NDVI, EVI, GEMI, SAVI, and bsVI are vegetation indices and were designed to show the characteristics of terrestrial biomass. For the purpose of burned area detection, the NBR-modified spectral indices (including NSEv1, NSEv2, NSTv1, and NSTv2) integrated the data of emissivity and LST in addition to the reflectance data. Based on the analysis of the spectral characteristics of the burned area and the unburned types, the optimal indicators applicable for burned area detection will be used as the feature vectors of the input layer of our BPNN.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Type** & **Multiple Threshold Criteria** & **References** \\ \hline Vegetation & NDVI \(>\) 0.3 & [42] \\ Cloud & (\((\rho_{1}+\rho_{2})>0.7\) and \(BT_{32}<285K\)) or (\((\rho_{1}+\rho_{2})>0.9\)) or (\(BT_{32}<265K\)) & [43; 44] \\ Bare soil & (NDVI \(<\) 0.2) and (\((\rho_{9}-\rho_{7})/(\rho_{9}+\rho_{7})\geq 0.1\)) & [45] \\ Water & (NDWI \(>\) 0) and (\(\rho_{2}<0.15\)) and (\(\rho_{7}<0.05\)) and (NDVI \(<\) 0) & [31; 49] \\ \hline \hline \end{tabular} \(\rho_{i}\) and \(BT_{i}\) refer to the reflectance and brightness temperature of band \(i\) respectively.  
\end{table}
Table 3: Multiple threshold criteria used to extract samples of unburned types and water masking.