## 4 Experimental Results and Discussion
### Visual Quality Comparison Before and After Texture Mapping  
While the vector-based processing approach exhibits superior performance in terms of efficiency and scalability, differences in texture mapping quality must also be considered. To evaluate these differences, a comparative analysis was conducted between Bing Maps, V-World, and the WIT method through visual inspection of rendered images (see Figure 10). Bing Maps and V-World are leading geospatial mapping platforms that employ cutting-edge technologies to ensure high-quality texture rendering and seamless user experience. Bing Maps utilizes multi-resolution texture mapping combined with progressive refinement techniques, allowing for smooth transitions across different zoom levels. Additionally, it employs hierarchical image tiling and lossless compression algorithms, ensuring efficient texture storage and retrieval. These methods enable Bing Maps to provide high-fidelity geospatial visualization with minimal performance overhead. V-World, as a nationally backed geospatial platform, integrates Cesium.js, a widely recognized WebGL-based 3D \begin{table}
\begin{tabular}{c c c c c} \hline
**Approach** & **1 st** & **2 nd** & **3 rd** & **Average \(\pm\) Std. Dev.** \\ \hline Raster-Based & 1.3 GB & 1.5 GB & 1.8 GB & 1.53 \(\pm\) 0.25 GB \\ Vector-Based & 38 MB & 45 MB & 50 MB & 44.3 \(\pm\) 6.0 MB \\ \hline \end{tabular}
\end{table} 
Table 16: Memory Consumption (GB/MB). \begin{table}
\begin{tabular}{c c c c} \hline
**No** & **Metric** & **Evaluation Standard** & **Result** \\ \hline
1 & Coordinate & Mean Error (ME), & \\  & Consistency & Maximum Error (MaxE) & \\
2 & Placement & Mean Positional Error & \\  & Accuracy & (MPE) \textless{} 100 m & 80 m \\
3 & Shape Accuracy &
\begin{tabular}{c} Shape Similarity Index \\ (SSI) \textgreater{} 0.9 \\ \end{tabular} & 0.92 \\ \hline \end{tabular}
\end{table} 
Table 17: Location Accuracy and Shape Consistency Evaluation. \begin{table}
\begin{tabular}{c c c c} \hline
**Approach** & **1 st** & **2 nd** & **3 rd** & **Average \(\pm\) Std. Dev.** \\ \hline Raster-Based & 2.2 & 2.8 & 3.2 & 2.73 \(\pm\) 0.51 \\ Vector-Based & 0.23 & 0.21 & 0.22 & 0.22 \(\pm\) 0.01 \\ \hline \end{tabular}
\end{table} 
Table 15: Query Response Time (seconds). rendering engine, to facilitate dynamic terrain visualization. This platform utilizes LOD (Level of Detail) optimization, photorealistic texture blending, and occlusion culling techniques, ensuring that high-resolution imagery is efficiently rendered without unnecessary computational load. Its terrain-adaptive rendering system dynamically adjusts texture resolution based on real-time user interaction, optimizing both performance and accuracy. Given the sophistication of these industry-standard approaches, the proposed WIT technique was evaluated against them to determine its potential improvements in texture optimization and spatial accuracy. The results indicate that vector-based processing significantly reduces texture inconsistencies and enhances visual coherence. By applying the WIT technique, high-resolution textures were optimized and interpolated, leading to smoother transitions and sharper details compared to conventional methods. Additionally, memory usage was reduced, and overall performance improved Table 18.  
The vector-based approach offers several advantages in real-time rendering and large-scale GIS data processing environments:  
* Preserved quality at high zoom levels without pixelation. * Dynamic resolution adjustment, enabling optimized rendering based on system resources. * Enhanced location-based accuracy through GPS performance optimization. These findings confirm that the vector-based WIT technique outperforms traditional raster-based mapping services, making it more suitable for real-time GIS applications and  
Figure 10: Comparative analysis of Bing Maps, V-World, and Wise Interpolated Texture.