Transmission of uncertainty of soil information in spatial analysis is an issue critical to digital soil assessment. To cope with the issue, coupling of the sequential Gaussian simulation (SGS) and the Latin hypercube sampling (LHS) methods, i.e., SGS-LHS, was proposed with a view to making full use of the advantages of the two methods as complementation to overcome their respective drawbacks, so as to improve accuracy and efficiency of the transmission and analysis of the uncertainty. The new method, (including two pathways: SGS-LHS1 and SGS-LHS2), SGS and LHS were tested in soil quality assessment of farmlands in Hong Kong for comparison. Results show that the uncertainty of the analysis using the SGS-LHS method was similar to that using SGS, but different to a certain, rather a big extent from that using LHS, and the combination method was approximate to SGS, but higher than LHS in accuracy, although LHS appeared to a little bit more accurate in terms of mean width of the confidential intervals. Therefore, the combined SGS-LHS method is recommended for analysis of transmission of soil information uncertainty in spatial analysis.