## 4 Results
### Spatial Zoning in the Su-Xi-Chang Region
#### 4.1.2 Spatial Zoning of the Su-Xi-Chang Region  
In the spatial multivariate logistic regression model of the Su-Xi-Chang region, the urban spatial attribute index (USAI) is the main indicator of spatial zoning. The Wald index is used to measure the major effects of various factors on urban spatial characteristics. The value 0.05 is taken as the evaluation standard for the confidence of the significance level. Moreover, the \(p\) value is chosen as 0.05 to represent the sampling and explain that the 5% chance of the relationship between this factor and the USAI is random. Therefore, the smaller the \(p\) value, the higher the credibility degree [48]. According to Table 3, the factors that have the greatest influence on urban spatial characteristics in the Su-Xi-Chang region are NTL and Road. The regression coefficient shows that the factors of nighttime light intensity, \(LST\), and traffic network density are negative. Subsequently, this indicates that the normalization of the evaluation value of these three factors is involved in the promotion of urban spatial characteristics. Moreover, \(GPP\) is positive, which indicates that the normalized evaluation value has a negative effect on urban spatial characteristics. According to results in Table 3, the multiple logistic regression model of the urban space in the Su-Xi-Chang region is:  
\[\text{lg}P=5.06-25.49\times X_{1}+6.01\times X_{2}-10.61\times X_{3}-5.16 \times X_{4} \tag{10}\]  
\[P=\frac{1}{1+\text{e}^{5.06-25.49\times X_{1}+6.01\times X_{2}-10.61\times X_{ 3}-5.16\times X_{4}}} \tag{11}\]  
As shown in Figure 4a, the Raster Calculator in ArcGIS is used to calculate the USAI with the factors of NTL, \(GPP\), \(LST\), and traffic network density. The spatial distribution of the USAI has a significant circle effect. The high-value distribution regions that show the USAI in jujube color are concentrated in Suzhou, Wuxi, Changzhou, and Kunshan. Furthermore, the high-value areas exhibiting urban spatial characteristics is particularly prominent and obvious. The high-value cluster areas of Suzhou and Kunshan have almost connected so as to form an entire high-value patch. Moreover, the median distribution region of the USAI in yellow and light blue is located in the periphery of the high-value distribution region and the zone between several high-value distribution regions. The transitional spatial characteristics are obvious and conform to the characteristics of the transition zone of the edge region. Finally, the distribution of the low value in dark blue is located in the peripheral area and water where the degree of human activity is low, which conforms to the characteristics of the ecological area. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variable** & **Regression Coefficient** & **Standard Error** & **Wald** & **Degree of Freedom** & **Significance** \\ \hline NTL (X\({}_{1}\)) & \(-25.49\) & \(1.74\) & \(215.49\) & \(1\) & \(<0.001\) \\ \(GPP\) (X\({}_{2}\)) & \(6.01\) & \(0.48\) & \(153.53\) & \(1\) & \(<0.001\) \\ Road (X\({}_{3}\)) & \(-10.61\) & \(1.13\) & \(88.80\) & \(1\) & \(<0.001\) \\ \(LST\) (X\({}_{4}\)) & \(-5.16\) & \(0.56\) & \(85.58\) & \(1\) & \(<0.001\) \\ intercept & \(5.06\) & \(0.29\) & \(308.41\) & \(1\) & \(<0.001\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Output results of the multiple logistic regression model. The USAI in the Su-Xi-Chang region is concentrated in the high section. The quantitative change rate of spatial features in the (0.08, 0.09) and (0.42, 0.43) sections exhibit obvious mutation points. Therefore, the boundary thresholds are set to 0.085 and 0.425 respectively. Due to the large number and serious fragmentation of landscape in the Su-Xi-Chang region contradict with the principle of continuity and integrity of the spatial zoning of urban agglomerations, 0.25 km\({}^{2}\) was taken as the smallest patch unit for the mentioned zoning results. Additionally, patch consolidation was carried out for each fragmented patch (Figure 4b).