Soils in vegetation-covered areas are of high variability in space and time, and the variability is crucial for hydro-geophysical processes at small and large scales. Conventionally, the spatial heterogeneity at large scale is visualized as a regional division map of soil properties by extrapolating sample measurements. No formalized method is available for assigning parameters for soils at the resolution of a small grid cell. This study formulates a method of establishing parameter space for vegetated soil by a single index (mu) derived from the unified grain size distribution (GSD). The index mu varies in space as a random variable and defines soil as a granular field. The mu-division represents the concentration of fine grains in response to root-soil interactions. Coupling mu-division with moisture distribution suggests that the gradient of mu plays a potential role in rooted soil hydraulics. It is further found that mu satisfies the Weibull distribution, which makes it possible to establish the mu-field for a soil space at large scale using the random dataset of mu. A case study is conducted in two vegetated slopes based on high-resolution digital elevation models (DEM) derived from unmanned aerial vehicle survey to create the field and illustrate its implications in morphology and hydrology. It is expected that the mu-field may derive parameter fields of various soil properties as functions of the GSD parameters and thus equip DEM with a complete dataset of soil. The paradigm proposed in the study fills the gap of establishing high-resolution data space for soil at large scale for dynamics of surface processes.