Comparison of IDW and Spline Interpolation for Topographic Accuracy Assessment Using Geomatics Approaches

The advancement of computer and software technologies has facilitated the widespread adoption of spatial analysis, particularly Geographic Information Systems (GIS), representing one of the most transformative developments in modern cartographic applications. GIS capture the geographical and non-geographical data in a way that allows for visual interpretation and analysis. In the present work, the study area of Al-Mada'in is examined along with the topographic surface accuracies obtained by the Inverse Distance Weighted (IDW) and Spline methods, based on the sampling points’ number (40) and the grid size of 30 m. This study compares different interpolation algorithms using their respective prediction mean errors, prediction Root Mean Squared Error (RMSE), and Standard Deviation (STD). The IDW method showed a maximum elevation value of 48.332 m and a minimum of 39.028 m with a mean of 44.265 m, an STD of 2.512 m, and an RMSE of 1.585 m. In contrast, the Spline method achieved a higher accuracy, recording a maximum value of 47.934 m and a minimum value of 39.453 m. It also achieved a mean value of 44.339 m, an STD of 2.345 m, and a lower RMSE of 1.531 m. According to the experimental findings on biased and normalized data, Spline outperformed the IDW approach as it demonstrated a more accurate and superior interpolation inside the sample space.