## 5 Discussion  
### Comparing Results with TM dNBR Map  
We assessed the accuracy of burned area maps produced with the TSM algorithm in two different regions. On 5 May 2003, there was a large forest fire in the Jinhe forestry region in Inner Mongolia, and on 17 May 2003, there was a large forest fire in the Shibazhan forestry region in Heilongjiang Province. The results of the GLASS and the MCD64 product were compared with the results of the fire using high spatial resolution Landsat images. Landsat TM data resolution is 30 m; its spatial detail features were more obvious compared to those of the 1000 m spatial resolution of the MODIS data. The green leaves of the fire area were reduced, and compared with the reflectance of normal growing forest, there was an increase in the SWIR spectral region and a NIR reflectance drop. Bi-temporal image differencing is frequently applied on pre-and post-fire NBR images, resulting in a differenced NBR (dNBR). Through the dNBR calculation results, statistics of the area and location of the fire and the fire condition in the subpixel of GLASS can be clearly determined. The results were sampled to 1000 m, and the detection accuracy of GLASS was evaluated on the basis of sampled results. Figure 7: Other types of forest disturbances and mean LAI (subscript is 1) and NBR (subscript is 2) time series of two verification regions. Region **A**: The maximum mean LAI in 2003 at a value of 2.1; maximum mean LAI was 4.1 for 2000 and 2001. Region **B**: The maximum mean LAI in 2003 at a value of 2.8; maximum mean LAI was 4.5 for 2000 and 2001. \[\mathrm{dNBR}=\left(\frac{\mathrm{B4-B7}}{\mathrm{B4+B7}}\right)_{\mathrm{pre-fire}}- \left(\frac{\mathrm{B4-B7}}{\mathrm{B4+B7}}\right)_{\mathrm{post-fire}} \tag{6}\]  
Landsat datasets for the study area were downloaded from the United States Geological Survey (USGS) satellite data download site. Data related to the May 2003 Jinhe fires were downloaded for 8 April 2003 (pre-fire) and 26 May 2003 (post-fire). Data related to the May 2003 Shibazhan fires were downloaded for 10 April 2003 (pre-fire) and 13 June 2003 (post-fire). The images were subjected to geometric, radiometric, and atmospheric correction. In Figure 8, the dNBR results are sampled to 1000 m spatial resolution using a mode resampling method. The statistical analysis of the sizes of the burned area before and after resampling and the burned area of the two study regions were reduced by different degrees after resampling. The burned area of the Jinhe was reduced by about 4000 hectares and the burned area of the Shibazhan was reduced by about 2000 hectares. Cloud and cloud shadow contamination will result in a dNBR calculation error. We identified cloud and cloud shadows in the Landsat images using visual interpretation, and a mask was applied to the GLASS and MCD64 to subset the image graphically to mask contaminated pixels. A reference of the burned area data for each region was compiled using high-resolution Landsat imagery. The results of the burned area of the two regions were compared using a confusion matrix to evaluate the spatial fidelity of mapping on a per-pixel basis. Table 2 provides the producer accuracy and user accuracies obtained when comparing GLASS and MCD64 versus reference maps of burned areas derived from Landsat TM over Jinhe and Shibazhan in the 2003 period. The overall accuracy is the percentage of all validation pixels correctly classified. The burned region map was validated using Landsat data. The TSM algorithm mapped the spatial distribution of the burns in Jinhe with an overall kappa coefficient of 0.776 and an accuracy of 96.5%; in Shibazhan, the overall accuracy was 98%, and the kappa coefficient was 0.838. The overall accuracy of the MCD64 product, when compared  
Figure 8: Regional images of the 2003 GLASS and Landsat fire disturbance in Shibazhan and Jinhe. The comparison results of two algorithms in Shibazhan are shown in the upper row: (**a**) TSM results; (**b**) Landsat image; (**c**) Landsat dNBR results.