Identifying Optimal Hiking Locations Using a GIS-Based Suitability Model

The growth of ecotourism and hiking is one pillar of Saudi Vision 2030. However, the Kingdom lacks an up-to-date national spatial classification that would enable systematic coverage and strategic decision-making on potentially suitable hiking areas. In response, this study developed a GIS-based MCDA framework to classify hiking zones and assess their suitability across mountainous, desert, and coastal environments. We integrated and processed spatial datasets, including topography (Digital Elevation Model; DEM), climate (temperature), Land Use/Land Cover (LULC), and proximity to infrastructure, using Inverse Distance Weighting (IDW) and Euclidean Distance. We classified the terrain into three environmental masks and used Zonal Statistics to characterize 96 established trails. Then we used the Rank Sum method to objectively weight the criteria. The model generated high-, medium-, and low-suitability maps, indicating that favorable hiking areas are especially found in hilly terrain. Comparison with existing SCHF trails showed general consistency between established trail characteristics and the modeled suitability patterns, supporting the framework’s potential as a national-scale spatial decision-support tool.