## 4 Experimental Results and Discussion  
### Analysis of Vector-Based Processing Results  
The first evaluation measures the average query response time per request for raster-based and vector-based data processing. The second evaluation assesses the memory consumption required for each approach. In the raster-based approach, the average query response time per request consists of the following:  
* 2 s for initial loading. * 0.2 s for searching. Additional time required due to memory allocation overhead. In the vector-based approach, the average query response time per request is the following:  
* 0.23 s for searching. Additional time required due to memory allocation overhead, though significantly lower than in the raster-based technique. Regarding memory consumption, the raster-based approach requires 1.3 GB, including the image loader, while the vector-based approach requires 38 MB, including the database connector. The performance of conventional raster-based models and vector-based interpolation models for 3D terrain information modeling is analyzed in an OpenGL 2.21.0 environment, as detailed in the following discussion. A comparative analysis of the two data processing approaches revealed no significant differences in the visualized model performance, as illustrated in Figure 9.  
In addition to the previously mentioned query response time and memory consumption, differences in data structure also influenced storage requirements. The detailed comparison of the two approaches is presented below in Table 14.  
Figure 9: Performance comparison of visualization between standard and interpolated models. The vector-based approach provides numerous advantages over the raster-based technique in terms of manageability and performance. It is considered a suitable method for cases where efficient resource utilization is required. To further verify the trends observed in the initial evaluation, two additional experiments were conducted using progressively more complex datasets. These tests aimed to assess the scalability of both raster-based and vector-based approaches in terms of query response time, memory consumption, and storage efficiency. In the second experiment, a dataset with a higher resolution and increased spatial complexity was used. The raster-based approach showed a proportional rise in processing time, with an initial loading time of 2.8 s and a retrieval time of 0.27 s. Memory consumption increased to 1.5 GB due to additional image data processing. Meanwhile, the vector-based approach remained efficient, with retrieval time slightly improving to 0.21 s due to optimized indexing and memory usage increasing modestly to 45 MB. The third experiment further escalated the dataset complexity, incorporating multi-layered spatial information. The raster-based model continued to experience performance degradation, with loading time increasing to 3.2 s and retrieval time reaching 0.31 s. Memory consumption also grew significantly to 1.8 GB, reflecting the limitations of fixed-size image storage. In contrast, the vector-based model maintained 0.22 s retrieval time and 50 MB memory usage, demonstrating its ability to efficiently handle more complex datasets Tables 15 and 16.