Robust methods are needed to assess tillage-induced changes in the physical quality of agricultural soils. Most soil physical quality (SPQ) evaluation procedures are based on the analysis of a limited number of soil cores randomly sampled in the soil profile. Such procedures likely fail to properly capture the spatial patterns in soil structure induced by tillage implements and vehicle traffic, resulting in a misleading SPQ diagnosis. We propose a hybrid method that couples high-resolution soil penetration resistance measurements with soil core sampling to derive high-resolution data grids of SPQ indicators encompassing the soil profile structural heterogeneity. The method builds on strong experimental relationships between soil penetration resistance and bulk density, and between bulk density and the soil hydraulic properties. We tested our method on a silt-loam soil with three tillage treatments (moldboard plowing, deep loosening with a tine cultivator, and minimum tillage), each including a zone impacted by the wheel traffic. The results allow visualization and analysissis of of the effect of tillage treatments and vehicle traffic on the soil SPQ indicators with a high level of spatial detail. The proposed methodology can be used to compare various soil management techniques or to monitor the temporal evolution of SPQ. As such, it can be a valuable tool to guide agricultural soil management. Furthermore, the generated high-resolution soil physical parameter grids could be used to parameterize numerical hydrodynamic models and estimate water and solute fluxes with distributed parameters representing the actual soil profile heterogeneity.