# A Spatio-Temporal Model for Forest Fire Detection Using HJ-IRS Satellite Data
## 5 Strengths and Limitations of the STM Method  
The STM method has some remarkable advantages. First, the background BT prediction is more accurate and robust than the contextual algorithm. The spatial heterogeneity has little effect on the forest fire detection result in STM. By using the STM, the algorithm is able to provide a satisfactory result in complex scenes. Second, the STM method takes full advantage of spatial contextual information and temporal information. The use of temporal information of the earth surface development is helpful for anomaly detection, which makes it possible for STM to detect more active fire pixels especially for small fire pixels. Moreover, a powerful competitive advantage of the STM method is that the window size has little influence on the measurement accuracy, whereas the window size is crucial in contextual tests. When there is a large fire and the image has a high-resolution, such as that of the HJ-IRS data, a \"cavity\" often appears in the detection area (Figure 14) in contextual tests. The primary reason is that there are not a sufficient number of valid neighboring pixels to predict background intensities with a limited window size. In addition, larger window sizes often result in a larger amount of calculations and problems of spatial heterogeneity. In our contrast experiments, there was not a cavity in the contextual detection result because the contextual tests included an absolute fire pixel judgment, which eliminated the \"cavity\". Regarding the spatio-temporal model, a potential fire pixel is regarded as a true fire pixel if the observed BT is higher than its neighboring pixels or its previous BTs. In other words, the relative fire pixel judgment is not only decided by the characteristics of the neighboring pixels but also by its previous characteristics. The integration of spatial contextual and temporal information allows the STM method to take full advantage of the two characteristics. In addition, background BTs calculated in the spatio-temporal domain are more robust, which can also mitigate the influence of the window size. Therefore, there were not \"cavity\" phenomena in the STM method results. A satisfactory result \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Data**} & \multirow{2}{*}{**Real Fire**} & \multicolumn{2}{c}{**Detected Fire Pixels**} & \multicolumn{2}{c}{**Commission Error (\%)**} & \multicolumn{2}{c}{**Omission Error (\%)**} \\ \cline{3-8}  & & **Contextual** & \multirow{2}{*}{**STM**} & \multirow{2}{*}{**Contextual**} & \multirow{2}{*}{**STM**} & \multirow{2}{*}{**STM**} & **Contextual** & \multirow{2}{*}{**STM**} \\  & & & **Algorithm** & & & & & \\ \hline
28 April 2009 & 196 & 228 & 223 & 18.86 & 14.80 & 5.61 & 3.06 \\
29 April 2009 & 3311 & 3329 & 3518 & 7.15 & 9.24 & 6.64 & 3.36 \\
03 May 2009 & 627 & 614 & 624 & 18.73 & 15.87 & 20.42 & 16.27 \\
11 May 2009 & 24 & 29 & 19 & 24.14 & 0 & 8.33 & 20.83 \\ Overall & 4158 & 4200 & 4384 & 9.45 & 9.91 & 8.68 & 5.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Accuracies of the STM method and contextual algorithm results. can be obtained using a small quantity of valid neighboring pixels in the STM method. This finding is verified in Figure 15. We can see that there is no positive connection between the number of fire pixels and the window size. Although the commission and omission errors decreased slowly with window size, small window sizes can lead to satisfactory results. In particular, we chose \(21\times 21\) as the optimal window size in this study because the omission error was smallest, and the commission error was acceptable when the window size was \(21\times 21\). Figure 14: The fire detection results using the contextual algorithm without the absolute fire pixel judgment produced a “cavity” in the detection area. The image was acquired on 29 April. Figure 15: Fire detection results of the image acquired on 29 April with different STM window sizes: (**a**) number of fire pixels; (**b**) commission error; and (**c**) omission error.