Weight adjustment of sampling sites is a key aspect for spatial allocation of samples in the accuracy evaluation of remote sensing classification. Taking accuracy evaluation of sampling sites in Shunyi District of Beijing as an example, a weight adjustment method of sampling sites integrating area attribute and uncertainty information was proposed and named fuzzy adjustment weight method, which was used for sampling sites layout of accuracy assessment. Firstly, the fuzzy neutral index and its weight were constructed to stand for uncertainty information, and the fuzzy adjustment weight was constructed by fusing the fuzzy neutral index weight and area weight, and the fuzzy adjustment weight results of each stratum were calculated to achieve spatial allocation of samples in the feature space. Secondly, different gradient sample sets were drawn, and spatial-simulated annealing and the minimization of the mean of the shortest distances criterion were used to optimize sampling sites in geographical space. Finally, the indexes of weight adjustment evaluation were constructed to assess the effect of fuzzy adjustment weights. The comparative analysis was achieved between fuzzy adjustment weight and the other weight adjustment methods and the methods without weight adjustment. The results showed that the fuzzy adjustment weights of large, medium and small uncertainty strata in Shunyi District were 0.45, 0.37 and 0.18, respectively. Compared with the area weights of each stratum, the weights of large and medium uncertainty strata were increased significantly and slightly, respectively, and the weight of small uncertainty stratum was decreased significantly. The overall accuracy, relative accuracy, root mean square error and standard deviation of the accuracy evaluation results for weight adjustment of five different sample sets were 69.90%~73.48%, 96.28%~99.82%, 0.01 and 0.01, respectively. The evaluated effect of fuzzy weight adjustment method was better than the methods with area weight, fuzzy neutral index weight, uncertainty stratification weight, and the spatial even sampling and simple random sampling methods. The weight adjustment of sampling sites for the developed method was more accurate and reliable. The developed fuzzy adjustment weight method used for sampling sites layout of accuracy assessment can integrate the area attribute and uncertainty information, and avoid excessive weight adjustment, which was used to improve the rationality for spatial allocation of sampling sites in each stratum.