## 4 Results and Analysis
### Validation Analysis  
The accuracy of building information extraction directly affects the determination of the earthquake catastrophe rate. In this study, stratified random sampling was used to validate the results of information extraction on building functions, story number, construction age, and structure type of buildings in the urban areas of Tangshan City. Firstly, according to the plot ratio of buildings in the block, the block is divided into five categories by using the natural breakpoint classification method in the urban areas of Tangshan City. Excluding the largest area and the smallest building area, 43 blocks were randomly selected from the remaining four categories. The location distribution of these 43 blocks is shown in Figure 18. Then, about 660 buildings were extracted from these blocks and used as sample buildings. The attribute information of each sample building, such as building function, story number, construction age, and structure type, was obtained as real data by manual determination using field research and street view photo assistance. The attribute information of the buildings obtained through this study is used as validation data. Finally, the real data and the validation data are compared, and the accuracy rate of the validation data is judged according to the confusion matrix, so as to verify the feasibility of the method of this study. Figure 17: Distribution map of structure type of buildings in Tangshan urban area. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Building Function** & **Story Number** & **Construction Age** & **Structure Type** \\ \hline  & 1–3 & Before 2001 & Masonry structure \\  & & After 2000 & Reinforcement concrete structure \\  & & Before 2011 & Brick and concrete structure \\  & 4–6 & After 2010 & Reinforcement concrete structure \\  & 7–9 & / & Reinforcement concrete structure \\  & 10–33 & / & Reinforcement concrete structure \\  & \(\geq\)34 floors & / & Reinforcement concrete structure \\ \hline Industrial buildings & 1 & / & Single-story industrial buildings \\  & \(\geq\)2 & / & Multi-story industrial buildings \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The corresponding relationship between the structure type, construction age, function, and story number of buildings in the urban areas of Tangshan City. Tables 4-7 show the confusion matrices for function, story number, construction age, and structure type, respectively. The element \(a_{i,j}\) in row \(i\) and column \(j\) of the table indicates the number of buildings manually judged as attribute \(j\) in the sampling survey and identified as attribute type \(i\) in this study. The element \(a_{i,j}\) in row \(i\) and column \(i\) is the number of buildings whose manually determined attributes in the sample survey and the attributes extracted in this study are the same. The accuracy rate in the table is the ratio of \(a_{i,j}\) to \(\sum_{j}a_{i,j}\), where \(\sum_{j}a_{i,j}\) is the total number of manually determined attributes of category \(i\). According to the results of the confusion matrix, the overall accuracy rates of building function, story number, structure type, and construction age are 88.62%, 86.65%, 86.49%, and 85.58%, respectively, and the accuracy of classification is measured by kappa coefficient. The values are all more than 0.8, which proves that the results of building information extraction are highly consistent and reliable.