Reliable Digital Terrain Modeling Using PPK GNSS Observations and Leveling-Constrained TIN Interpolation
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Reliable Digital Terrain Models (DTMs) are crucial for most engineering and environmental applications, especially where accurate elevation is required. While conventional leveling offers high vertical accuracy, it needs long time periods, causing high work costs, particularly for wide regions. GNSS-based methods that provide fast data acquisition may serve as an effective alternative; however, achieving reliable vertical accuracy remains a challenge. Accordingly, this study proposed a practical approach that integrates the Post-Processed Kinematic GNSS technique with Constrained Triangulated Irregular Network (TIN) modeling to improve elevation accuracy. In this method, accurate leveling cross sections distributed along the study area are used as vertical constraints to improve interpolation reliability. The performance of the model is validated using independent cross-section data observed using precise leveling. Statistical analysis demonstrates a strong correlation between generated DTM elevations and leveling data, evidenced by a coefficient of determination (R²) of 0.9915 and a vertical RMSE of 0.0608 m, with residuals mainly within ±0.10 m for the majority of observations. The results validated that the Constrained TIN modeling method effectively maintains the accuracy of PPK-derived elevations and decreases vertical discrepancies. The proposed methodology, integrating PPK observations with constrained TIN modeling, achieves reliable decimeter-level vertical accuracy, making it appropriate for various engineering and environmental applications that needs high-precision terrain representation.
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