In Fengqiu County of Henan Province, topsoil samples were collected from 3 608 sampling sites, of which 3 463 sampling sites were chosen to form a master dataset for soil attribute mapping, while the remaining 145 sampling sites were to form a master verification dataset. Then, through 4%~96% multi-scaled stochastic sampling of the former, 17 subsets were formed for mapping of soil organic matter, soil available phosphate and soil readily available potassium using kriging interpolation, inverse distance weight interpolation (IDW) and Polygon value represented by point value (PRP), respectively. Based on direct map comparison between the computerized mapping subsets and the master mapping dataset, correlation coefficients were obtained to evaluate effects of scaling on soil attribute maps, and further more comparison was made with the multi-scaled mapping evaluated with the verification dataset. In the end, variable coefficient of the multi-subset mapping was used to indicate uncertainty of the expression of multi-scaped mapping and comparison was made of this uncertainty with that of the kriging variance and that of the stochastic simulation. Through the direct map comparison, it was found that the relationship between mapping quality and volume of samples was fractal and the fractal dimension was affected dually by mapping method and spatial variability of soil attributes. In the same conditions, the fractal dimension was the smallest with the kriging method and the largest with the PRP method, and the smallest with soil available potassium and the largest with soil available phosphate. The correlation coefficients and Root mean square error(RMSE) between the measured values and forecasted values in the verification dataset did not show any fractal feature as expected. The uncertainty of single-scale mapping expressed by kriging variance and stochastic simulation was significantly influenced by distribution of the sampling sites and value of the kriging estimation, while the uncertainty of the multi-scale mapping based on direct map comparison reflected more objectively natural variation of soil attributes, among which soil organic matter and soil available potassium showed more obvious laws in variation, while soil available phosphate didn’t .