Urban park use is a key indicator of sustainable urban development, reflecting the accessibility and social value of urban green infrastructure. However, existing studies often struggle to distinguish stable spatial differences from short-term temporal dynamics. Using monthly data for 125 urban parks in Las Vegas from 2022 to 2024, this study examines how park visitation is shaped by spatial, temporal, and contextual factors. It addresses three objectives: identifying cross-park determinants of visitation, examining within-park monthly dynamics, and assessing spatial variation in key relationships. Park visitation is measured using observed visit counts, with dwell time and travel distance used as alternative behavioral outcomes for robustness tests. To address these research questions, this study asks: (1) what structural and contextual factors explain cross-park differences in park visitation; (2) how park visitation responds to changing contextual conditions within parks over time at the monthly scale; and (3) whether the relationships between park visitation and its key determinants vary across space. To answer these questions, the analysis combines annual cross-sectional ordinary least squares (OLS) regression, monthly panel models, Random Forest analysis, robustness tests, and geographically weighted regression. This study employs a triangulated analytical framework combining cross-sectional ordinary least squares (OLS) regression monthly fixed-effects (FE) panel models, and Random Forest (RF) analysis. These factors function as stable support for sustainable park use. Crime exposure shows no stable global linear effect, but its association with visitation appears conditional on temporal and spatial context. Overall, the findings suggest that park visitation is shaped by the interaction of physical design, safety conditions, and urban context. By explicitly separating cross-sectional spatial and economic inequalities from within-park temporal dynamics, this study offers policy-relevant evidence for urban planners and park managers seeking to promote more inclusive, efficient, and sustainable urban park systems through integrated design, economic activation, and safety-oriented interventions.

The rapid reshoring of semiconductor manufacturing in the United States has introduced large-scale, energy-intensive industrial facilities into metropolitan regions increasingly exposed to climate-related infrastructure pressures. While existing research on industrial development often emphasizes agglomeration-driven economic spillovers, less attention has been given to how the early operational period of such facilities corresponds with surrounding commercial activity, particularly in peri-urban and greenfield suburban contexts. This study examines the spatiotemporal dynamics of localized commercial vitality surrounding semiconductor fabrication facilities in Phoenix, Arizona, and Austin, Texas. High-frequency point-of-interest (POI) mobility data are used to measure localized commercial activity, while regional electricity load records provide contextual information on metropolitan-scale demand conditions. Using a comparative Difference-in-Differences (DiD) framework combined with distance-band analysis and sectoral-temporal stratification, the study evaluates activity patterns between 2020 and 2025. The results indicate that the early operational period of the Phoenix facility is associated with a sustained relative divergence in mobility-derived commercial activity compared with the Austin benchmark trajectory. Spatial analysis identifies a clear distance-dependent gradient, with the largest relative reductions concentrated in intermediate suburban zones rather than immediately adjacent to the facility. Sectoral and temporal analyses further show larger reductions in dining and nighttime activity than in routine retail and daytime activity. Overall, the findings suggest that the early operational period of large industrial mega-projects may be associated with differentiated commercial activity trajectories across surrounding suburban environments. More broadly, the study demonstrates how high-frequency mobility data can be used to examine spatiotemporal variation in commercial vitality around major industrial developments.