A Methodological Approach to the Restoration of a Rural Street Using Affordable Digital Technologies

Accurate spatial data is essential for the effective planning and restoration of rural streets, which are linear elements within settlements. This study evaluates the applicability of digital street models to landscape architecture, focusing on the precision and efficiency of three data acquisition methods: terrestrial laser scanning (TLS), aerial photogrammetry using an unmanned aerial vehicle (UAV), and close-range photogrammetry (CRP) using a smartphone. TLS was used as the reference method due to its high local geometric accuracy, while UAV and CRP were assessed as low-cost alternatives. We conducted field data collection, digital model processing, and a comparative analysis of accuracy, cost, and time requirements. TLS achieved high precision, with 85% of measured points within ±0.5 cm; however, it produced data gaps due to scanning obstacles. UAV-derived models demonstrated 93% agreement with TLS and offered more complete coverage, making it a more efficient option for overall mapping. CRP models showed only 34% compliance with TLS but provided superior texture detail. However, their limited geometric accuracy and risk of deformation constrain their use in visualizing specific elements. Among the low-cost methods, the UAV is the most suitable for generating models usable in GIS and CAD environments. A combined approach—using a UAV for accurate geometry and CRP for detailed textures—offers a cost-effective strategy for enhancing model quality in landscape architectural applications.