Understanding the spatial autocorrelation characteristics of the distribution of economic fish is helpful to reveal the distribution pattern of its habitat and the formation mechanism of fishing grounds, which provides a basis for the evaluation and rational exploitation of the resources. Due to long-term overfishing, the fishery resources in the northern South China Sea have declined seriously, especially in the shallow area of 100-m isobath. As an important fishing target of bottom trawling in the South China Sea, the resources of Priacanthus spp. are under great pressure, so exploring the pattern characteristics of the spatial distribution of the resources can provide a certain reference basis for the sustainable utilization and scientific management of the resources. However, some studies denied that the spatial autocorrelation was affected by the spatial scope of the study area, and the spatial autocorrelation varied greatly under different analysis scales, thus weakening the actual effect of fishery resources assessment and scientific management. Therefore, based on the data of bottom trawl fishery in the northern South China Sea by a fishery information network from 2009 to 2014, this study used the methods of global spatial autocorrelation and local spatial autocorrelation to analyze the dynamic changes of spatial autocorrelation of Priacanthus spp. resources. And the incremental spatial autocorrelation analysis was added to improve the accuracy of the research results. The results were as follows: ① the results of global spatial autocorrelation analysis showed that in the whole study area, the interannual resources of Priacanthus spp. were mainly in low-density area and less in high-density area. ② according to the incremental spatial autocorrelation analysis, the resources of Priacanthus spp. showed a strong spatial autocorrelation within the scale of 76-87 km, and showed a significant aggregation distribution pattern. ③ the local spatial autocorrelation analysis showed that the distribution of hot and cold spots of Priacanthus spp. resources varied greatly from year to year, and the hot spot fishing areas were mainly concentrated between the 50-m and 100-m isobath in the middle part of the study area. The cold spot fishing areas were concentrated in the sea area near the 50-m isobath. In this paper, the incremental spatial autocorrelation method was introduced to explore the spatial autocorrelation of Priacanthus spp. resources, which provided a new idea for mining the temporal and spatial distribution characteristics of fishery resources.