Xinjiang is characterized by a typical arid–oasis geographical setting, with complex interactions between tourism development and improvements in the human settlement environment. Taking 14 prefecture-level administrative units in Xinjiang as the study units, this study constructs panel data on the tourism industry and human settlement environment from 2013 to 2025. The entropy weighting method, coupling coordination degree model, spatial autocorrelation analysis, and obstacle degree model are employed to examine the spatiotemporal characteristics and obstacle factors of coordinated development between the two systems. The results show that: (1) From 2013 to 2025, the overall development levels of Xinjiang’s tourism industry and human settlement environment improved, although pronounced regional disparities remained. (2) The coupling coordination degree increased from 0.2406 in 2013 to 0.3512 in 2025. During the COVID-19 pandemic period, most regions experienced fluctuations, with the tourism industry system exhibiting greater variation than the human settlement environment system. (3) Spatial analysis indicates that no significant overall spatial clustering pattern has formed across Xinjiang, although local high-value clusters are present in Urumqi and its neighboring areas. (4) Indicators including the urban water supply coverage rate, urban sewage treatment rate, passenger turnover, operating revenue of catering enterprises above the designated size, and inbound tourism revenue consistently rank among the major obstacle factors, with differences in obstacle characteristics across regions. This study concludes that the coordinated development of Xinjiang’s tourism industry and human settlement environment is jointly influenced by resource and environmental conditions, regional development foundations, and the operational capacity of the tourism industry. Accordingly, regional differences should be taken into account when improving infrastructure, enhancing the quality and efficiency of the tourism industry, and implementing differentiated optimization strategies.
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Zhang et al. (2026) studied this question.
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