Based on tourism digital data of Shenzhen from 2020 to 2024, this study takes local and non-local tourists as research objects, selects representative tourism nodes, and constructs their respective tourism flow networks. Using social network analysis, the spatial characteristics and differences of the tourism flow network structures of the two groups are compared and revealed. From the perspective of human-environment interaction theory, the interactive responses between different tourist groups and the tourism environment are explored. The results show that: ① In terms of node attractiveness, there is a significant "group-environment" interactive difference: The core of the local tourist network is dominated by natural nodes, reflecting urban residents’ intrinsic need for "human-environment harmony" through natural regulation to alleviate daily spatial pressure; whereas the core of the non-local tourist network is mainly composed of humanistic nodes, indicating their "place identity" with and symbolic consumption of Shenzhen’s modern and international urban image, with the influence of humanistic nodes continuing to increase; ② In behavioral patterns, local tourists exhibit relatively singular travel paths, showing "place attachment" to familiar environments; non-local tourists organize more diverse itineraries with a high proportion of humanistic nodes, aligning more with the characteristics of "place consumption"; ③ In spatial structure, local flows show a pattern of "denser in the east, sparser in the west; stronger in the south, weaker in the north," highly concentrated in Dapeng New District; non-local flows are characterized as "denser in the west, sparser in the east," highly concentrated in Nanshan District, while also diffusing toward the natural areas of Dapeng. Overall, districts such as Bao’an, Longgang, Pingshan, Longhua, and Guangming show weaker tourism development and unbalanced spatial connectivity. This study suggests that Dapeng New District, as a convergence zone of natural and humanistic resources, has the potential to promote the coordination of Shenzhen’s tourism human-environment system and balanced spatial development. Future efforts should focus on optimizing resource supply, strengthening regional linkages, and guiding the formation of a healthier and more sustainable tourism human-environment relationship.

The high-quality development of rural tourism in the Yellow River Basin has become a powerful starting point for the implementation of the rural revitalization strategy and the ecological protection and high-quality development strategy of the Yellow River Basin. In this study, 386 key villages of rural tourism in the Yellow River Basin were used as sample points, and geospatial analysis methods were used to study the spatial pattern and differences of rural tourism and its network attention in the Yellow River Basin. It is found that: ① The key villages of rural tourism in the Yellow River Basin and their network attention are concentrated in spatial distribution. The key villages of rural tourism have formed five major agglomeration areas in the Ganqing junction area, northern Ningxia, northern Henan, central Shandong and central Sichuan, and the network attention is concentrated in central Shandong, central Sichuan, northern Ningxia and central Shaanxi, while the attention of Inner Mongolia, western Gansu and western Qinghai is low, and no obvious agglomeration has been formed. ② There were spatial differences in the agglomeration distribution of rural tourism key villages and network attention, the key villages of rural tourism in central Shandong, central Sichuan and northern Ningxia showed high concentration, the key villages of rural tourism in Ganqing junction were clustered but the network attention was low and scattered, the number of rural tourism key villages in central Shaanxi was small but the network attention was highly concentrated, and the spatial agglomeration and network attention of key villages in Inner Mongolia, western Qinghai and northern Shaanxi were low. ③ There were obvious differences in spatial correlation between key villages of rural tourism and their network attention, and the distribution of cold and hot spots in key villages of rural tourism in the Yellow River Basin and the distribution of cold and hot spots of network attention were inverted. According to the conclusions of the study, the suggestions for the optimization of the spatial pattern and marketing management of rural tourism are put forward.