Accurate land surveys are fundamental for optimal building planning, as topography bridges architecture and landscape. This paper proposes a Digital Feature Model (DFM) that integrates UAV photogrammetry and LiDAR data to optimize terrain mapping. UAV photogrammetry provides high-accuracy mapping of textured anthropic surfaces, while LiDAR excels in penetrating vegetation-covered areas. By segmenting and fusing datasets from both sensors, the DFM enhances accuracy across diverse terrain conditions. In a built environment case study, 233 measured points representing ground, vegetation, and anthropic features were analyzed to validate the methodology. The DFM achieved a vertical RMSE of 0.075 m, outperforming the photogrammetry and LiDAR models with RMSEs of 0.209 and 0.130 m. This approach improves field data reliability, enabling the creation of accurate topographic plans and subsequent GIS spatial analyses critical for optimal building planning and sustainable land development.