Spatiotemporal Effects and Nonlinear Characteristics of Mechanisms Driving Street Vitality in Historic Districts: A Multi-Source Data-Driven Approach

Preservation and revitalization of historic districts are critical for quality urban development and renewal. Accurately assessing what drives district vitality is essential for sustainable historic area development. Current research often uses cross-sectional data and single models, limiting understanding. This study uses Xigong District, Luoyang, and integrates multi-source data—street view imagery, points of interest, road networks, and nighttime lighting—from 2014 to 2021. MGWR and XGBoost models create a dynamic framework for analyzing how the built environment affects street vitality over time. Results: (1) Spatial effects: Physically, green exposure, functional mix, and road network access are highly spatially sensitive. Morphological indicators—commercial frontage, street continuity, complexity, and building texture—show reduced local variation over time. Perceptually, the influence of abstract color narrows each year, and subjective preference broadens. (2) Nonlinear effects: Green exposure and openness dominate but show negative inhibition and diminishing returns. Morphological, functional, and road network indicators have moderate explanatory power with clear thresholds. Perceptual importance shifts from abstract color to architectural texture, which now rises while color influence steadies. Renewal should go beyond basic greening and surface color. Instead, focus on refined, threshold-based control of form and function, and preserve authentic historic texture. This approach enables scientific, sustainable vitality.