Accurate elevation information is essential for effective recreational cycling route planning, particularly in nonurban and forested terrains. This study evaluates the vertical accuracy of Türkiye’s national elevation model (General Directorate of Mapping HGM Küre), compared with the widely used Google Elevation Application Programming Interface (API), using the Türkiye Geoid 2003 -referenced Global Navigation Satellite System (GNSS) field measurements as ground-truth. A total of 83 elevation points were collected along a forested cycling route and analyzed using descriptive statistics, Bland–Altman plots, and Kruskal–Wallis tests to quantify elevation discrepancies across different topographic zones. The results reveal statistically significant differences in elevation accuracy between the models, with the HGM Küre and Google Elevation API showing elevated error and variability in vegetated and sloped areas. Of note, HGM Küre exhibited systematic overestimations; the Google Elevation API data demonstrated higher scatter. These findings underscore that elevation model performance is highly context-dependent, and unvalidated data sets can misrepresent terrain conditions crucial to cyclist safety and route efficiency. By highlighting the limitations of current digital elevation models and the potential of national models such as HGM Küre when calibrated with GNSS data, this study fills a notable gap in the literature. It provides practical guidance for transportation planners, suggesting a hybrid approach that integrates field-validated data for more accurate and context-aware route planning.
Kocaman et al. (Sat,) studied this question.
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