## 4 Results
### Experimental Design and Comparative Methods
#### 4.1.3 Comparative Methods
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Rank** & **Connective** & \(\mathbf{C_{1}}\) & \(\mathbf{C_{2}}\) & \(\mathbf{C_{3}}\) & **Our Method** \\ \hline
0 & 5360 & 1480 & 2231.644 & 422.5701 & 1309.227 \\
1 & 5364 & 1481 & 2230.939 & 420.026 & 1348.485 \\
2 & 5362 & 1478 & 2230.087 & 425.0908 & 1409.523 \\
3 & 5362 & 1485 & 2231.759 & 416.1231 & 1471.457 \\
4 & 5360 & 1492 & 2233.074 & 411.8533 & 1543.956 \\
5 & 5358 & 1492 & 2233.3 & 425.2387 & 1546.369 \\
6 & 5354 & 1499 & 2233.493 & 405.1632 & 1594.553 \\
7 & 5350 & 1501 & 2233.887 & 398.5223 & 1611.594 \\
8 & 5354 & 1498 & 2234.167 & 407.9621 & 1619.731 \\
9 & 5354 & 1498 & 2233.201 & 402.3584 & 1621.168 \\
10 & 5358 & 1498 & 2236.101 & 411.7799 & 1629.375 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The measurement values of information content under different levels of disorder. Figure 8: Simulated dataset of disordered arrangements of building objects. unable to effectively distinguish the increasing trend of information content caused by the disordered arrangement of spatial objects. However, the proposed method benefits from the introduction of similarity analysis theory and visual repetition limited growth theory, enabling it to effectively identify the degree of disorder in spatial distribution and effectively eliminate redundant information caused by the similarity and regular arrangement of buildings. In the application of crowdsourced vector data with a large number of regularly arranged buildings, our method can effectively improve the accuracy of spatial information measurement. Additionally, the method proposed in this paper breaks through the limitations of map size, enabling the calculation standards of information content to be unified across different map sizes. Experiment 2: Consistency Analysis of the Simplification Level of Area Maps and Spatial Information Content  
To further validate the impact of geometric information changes on spatial information and evaluate the accuracy and comprehensiveness of the method proposed in this paper, natural feature objects with complex morphological characteristics and irregular arrangements were selected as experimental data. Using simplification operators, a simulation process of the gradual attenuation of information content was achieved, and a simulated dataset with a priori information on changes in information content was designed. Experimental data are shown in Figure 9.  
Based on the experimental assumption that simplification processing has a diminishing effect on the spatial information of area maps, i.e., as the degree of simplification increases, the spatial information in the map decreases accordingly, we expect that with the deepening of simplification, the measurement value of spatial information in area maps should gradually decline. Based on this assumption, this paper simulates the reduction and weakening process of spatial information through varying degrees of simplification for lake maps with complex geometric morphological characteristics. Ten consecutive simplification processes were conducted using the \"POINT_REMOVE\" method in ArcGIS, and the simplification intensity was controlled by adjusting the minimum area tolerance parameter. The parameter range varied from 0.00001 to 0.0001, providing ten intensity levels from low to high. Figure 10 shows the simplification results for two typical area objects. After simplification, the number of points in the lake objects of this layer decreased from 100% of the original layer to 45.5%, thus removing 54.5% of the points. Figure 9: Area maps of natural objects with complex morphological characteristics. As shown in Table 4, for the continuous simplification process of area maps, both the proposed method and [PERSON]'s method can identify the attenuation of spatial information, while [PERSON]'s method cannot effectively measure the attenuation of spatial geometric information due to the characteristics of Shannon entropy.