(untitled) (FIG Joint Land Administration Conference, 2025)
Property valuation requires the consideration of multiple factors, with locational attributes playing a decisive role in explaining market heterogeneity. Despite their relevance, the use of locational variables in mass appraisal models still lacks conceptual standardization, limiting their integration into international land administration frameworks. This study aims to propose a conceptual classification of locational variables based on a systematic review of international literature. A total of 55 articles published between 2015 and 2025 were analyzed, applying Natural Language Processing (NLP) techniques and semantic clustering to identify, normalize, and categorize variables. The analysis resulted in seven main categories: geographic coordinates, spatial units, central accessibility, public transportation, urban services and amenities, environmental features, and neighborhood socioeconomic context. Among these categories, the most frequent variables were associated with urban services (54.5% of the studies), public transportation (43.6%), and central accessibility (27.3%). In total, more than 120 distinct locational variables were identified and normalized, with the most recurrent being proximity to schools (36%), hospitals (33%), commercial centers (27%), public transportation (metro/train stations in 24% and bus stops in 16%), and the city center (31%). The categories variables were then integrated into the Valuation Package of ISO 19152-4 (LADM), considering exclusively the two-dimensional (2D) context traditionally applied in urban mass appraisal. This systematization reinforces the potential for adopting a standardized and interoperable model, while opening the path for future extensions to 3D contexts. The results demonstrate that the conceptual structuring of locational variables enhances transparency, comparability, and applicability of mass appraisal models, aligning empirical practices with international land administration standards.