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Weight adjustment of the sampling sites is an important means of the statistical inference for the global mean of sampling sites attributes. Taking the sampling sites of agricultural land in Shunyi District, Beijing as an example, weight adjustment method (Thiessen polygon weight adjustment method) of sampling sites for global mean estimation was proposed. Firstly, the type division rules of sampling sites were constructed to divide the sampling sites into aggregated, sparse and even sampling sites. Secondly, weight adjustment amounts and adjustment rules for different types of sampling sites were determined, and the weights of the sampling sites were adjusted, respectively. Finally, taking soil heavy metal Hg content and NDVI data of agricultural land as an example, a comparative experiment between Thiessen polygon weight adjustment method and the original sampling sites (without weight adjustment) and the conventional area ratio weight adjustment method was set up to quantitatively evaluate the global mean estimation effect of different weight adjustment methods based on the relative errors of two evaluation parameters. The results suggested that the weights of the two aggregated sampling sites were reduced, and the weights were 0.609 and 0.883, respectively. The weight of one sparse sampling site was increased, and the weights was 1.068. The weights of sixty-three even sampling sites remained unchanged, and the weights of each sampling sites was 1. The relative errors (0.413%, 1.617%) of the global mean estimated by the Thiessen polygon weight adjustment method statistical inference were smaller than those of estimated by the original sampling sites (1.056%, 2.500%) and the conventional area proportional weight adjustment method (2.933%, 2.941%), respectively. It was shown that the global mean estimation of the sampling sites for the Thiessen polygon weight adjustment method was much more accurate and reliable.