## 4 Results
### Experimental Design and Comparative Methods
#### 4.1.3 Comparative Methods  
Since the method proposed in this paper aims to measure the spatial information of areal maps, two existing comprehensive measurement methods (Li and Liu) are selected as comparison methods [16; 17]. Additionally, a measurement method for the topological information of geospatial data is also used for comparison with the experimental results [15]. Detailed information is presented in Table 1 below:  
Experiment 1: Consistency Analysis of Spatial Information Content and the Degree of Disorderly Arrangement of Area objects  
A dataset with gradually increasing degrees of disorder in building arrangement is designed to simulate the continuous change process of the spatial distribution of area maps evolving from regularity to irregularity. This is intended to verify the consistency between the proposed spatial information measurement method and the degree of disorder in the arrangement of buildings. As the irregular arrangement of buildings only involves spatial distribution without any changes in geometric information, for the purpose of controlling variables, three spatial distribution information measurement methods were employed as comparative methods in Experiment 1. The experimental data were selected from real vector data on the OSM platform. Different degrees of the disordered arrangement of area objects were simulated by changing their positions and directions. The design of the simulated data involved gradually increasing the proportion and intensity of disorder to alter the original regular arrangement pattern of the objects. A total of 10 levels of disorder intensity, ranging from a variance of 0.1 to 1.0, were used to create a dataset of 11 area maps, including the original data, with known orders of information content. The experimental setup is shown in Figure 8.  
\begin{table}
\begin{tabular}{p{128.0 pt} p{128.0 pt} p{128.0 pt}} \hline \hline
**Method** & **Calculation Formula** & **Description** \\ \hline [PERSON]’s methods for spatial distribution information & \(C_{1}=\frac{N_{connect}}{M}\) & “\(N_{connect}\)” represents the node degree; \(M\) represents the total number of connecting edges in a map. \\ \hline [PERSON]’s methods for spatial geometric information & \(I_{1}=-\sum\limits_{i=1}^{N}\left(\frac{s_{i}}{5}\right)\log_{2}(\frac{s_{i}}{5}  
The experimental results are shown in Tables 2 and 3. Based on the correlation analysis between the measurement results of information content and the degree of disorder, the correlation coefficients between the measured values of the four methods and the degree of disorder are as follows: \(C_{1}\): 0.90; \(C_{2}\): 0.86; \(C_{3}\): \(-\)0.70; ours: 0.95. The method proposed in this paper exhibits the best agreement trend in terms of correlation with the degree of disorder. While it is true that methods \(C_{1}\) and \(C_{2}\) also demonstrate strong correlation in the correlation analysis, a comparison of the variation ranges of the information content reveals that the current variation rates of the information content measures for both comparison methods are less than 2%, falling within the range of calculation errors. Consequently, they exhibit insensitivity to the differences in information content variation caused by disordered arrangements. Currently, only the proposed method can effectively distinguish changes in the degree of disorder in the arrangement pattern of areal features. As can be seen from Tables 2 and 3, the existing representative methods have not considered the similarity and regular arrangement of building objects. Therefore, they are