Altimetric assessment of topodata in complex terrains with GNSS-RTK validation (global navigation satellite system – real-time kinematic)

This study evaluates the altimetric accuracy of the TOPODATA Digital Elevation Model (DEM), derived from the Shuttle Radar Topography Mission (SRTM), through comparison with GNSS-RTK data in an area of high topographic variability. The analysis was conducted in Cachoeira do Lepa, located in the municipality of Canguçu, Rio Grande do Sul (Brazil), a region characterized by pronounced altimetric breaks over short distances. A total of 306 georeferenced points were used, and spatial statistical analyses were applied. The results revealed systematic discrepancies, with a tendency of the TOPODATA to underestimate elevations, showing a mean bias error (MBE) of 3.15 m, mean absolute error (MAE) of 3.57 m, and root mean square error (RMSE) of 4.33 m. Spatial autocorrelation was significant (Moran’s I = 0.771; p < 0.001), reducing the effective degrees of freedom (Dutilleul: 120.4) and requiring robust tests (Brunner–Munzel: p < 0.0001; Cliff’s Delta = 0.60). Accuracy varied with elevation: low-lying areas presented an MBE of 0.75 m, while higher terrains reached 6.02 m (Kruskal–Wallis: p < 0.0001). Spatial cross-validation indicated an RMSE of 5.18 m (95% CI: 3.68–6.30 m), and Spearman’s correlation was weak (ρ = –0.077; p = 0.125). It is concluded that TOPODATA tends to underestimate elevations, with larger errors in higher terrains, limiting its reliability for micro-scale applications. The study highlights the methodological risks of using generalized DEMs in morphologically complex regions and suggests hybrid approaches supported by field data as an alternative. The findings align with the United Nations Sustainable Development Goals (SDGs), particularly in the context of precision agriculture, sustainable urban planning, and climate action.