Revealing the dynamic changes in the spatiotemporal patterns of tourist movement is crucial for optimizing sustainable development strategies in tourist destinations. This study employs an enhanced DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm alongside a method for interpreting spatiotemporal patterns. Utilizing this approach, we analyze extensive trajectory data from 2018 to 2021 to identify changes in the spatiotemporal patterns of tourists in the Kubuqi Desert, a representative desert tourism destination in China. Our findings reveal a significant increase in average travel distance (+274.3%) and a decrease in travel time (-8.8%) during the second period (2020-2021). Eight patterns were identified in the first period (2018-2019), whereas only five were recognized in the second period, indicating a reduction in pattern heterogeneity. The tourism areas became more compact in the second period and expanded westward with the emergence of new tourist cities. Finally, we discuss the implications of these findings.