Efectos del tipo de suelo sobre las características de las huellas de calzado en el Alto Valle de Rio Negro y sus implicancias en la criminalística

Abstract

The identification and comparison of footwear impressions is a key tool in criminal investigations, as it can link a crime scene to a suspect or rule out possible matches. However, the physical characteristics of the substrate on which the impression is made can cause distortions that affect its forensic interpretation. This study aimed to analyse the effect of two soil types, clay and sand, influence the dimensions and geometric patterns of shoeprints, and to evaluate their impact on the reliability of footwear comparison. Three moderately worn shoe models (Puma, Vans, and Under Armour) were used to create controlled impressions on clay and sandy soils, simulating forensic conditions. Photographic records were used to measure the length and width of each complete footprint as well as the surface area of specific geometric tread patterns. Measurements were obtained using ImageJ software, and statistical analyses were performed to assess significant differences between soil and footwear types. The results show that soil type significantly affects footprint dimensions. Clay soil, in particular, caused greater distortion, with some patterns expanding by up to 41%. Closed patterns such as hexagons (in Vans shoes) tended to retain their shape more consistently than open shapes such as rectangles or inverted “U” patterns (Puma and Under Armour). Variations in total footprint length and width were also observed, being more pronounced in clay soil and in the Under Armour model. These findings indicate that the physical properties of the substrate directly influence the fidelity of the impression and the feasibility of accurate comparisons. From a forensic perspective, this highlights the need to develop correction factors and regional protocols that take into account terrain variability. This research provides original data on the soils of the Alto Valle de Río Negro and contributes to improving the interpretation of this type of evidence in real-case scenarios.