Abstract: [Objective]Sample general distribution feature is a major factor to impact sample size, and normal transformation for non-normal distribution of general samples is an effective means to reduce sample size and improve survey efficiency. [Method]By using the special distribution data of the cultivated land of Mainland China of 2005 and by taking 1:100,000 topographic map frames as sampling units, the paper calculates the proportion of cultivated land area in each map frames. The normal transformation of original data is conducted by calculating 1.5 times square root, 2 times square root, 2.5 times square root, 3 times square root, and 4 times square root of them. Based on above transformation, a contrastive analysis on the factors of kurtosis and skewness, the number of samples and sampling error before and after the transformation is conducted. [Result]The result shows that, the stratified sampling based on 2.5 square root operation can dramatically reduce sampling rate. The sampling rate is reduced from 92.26% to 22.55%, and the average relative error of cultivated area index is reduced from 7.06% to 5.66%. The accuracy of sampling method is verified by using the 2005 cultivated land area index, and the average relative error of the sampling is only 3.27%. [Conclusion]The sampling method proposed by the study is highly applicable, and it is necessary to make normal transformation on the data distribution in spatial sampling. The study result has provided useful reference for the researches of scholars on space sampling survey.