Based on multi-source data including mobile signaling data and remote sensing imagery, this research constructed human activity indicators and applied spatial analysis methods to identify gender-specific patterns in green space usage across different types of days. A Standardized Gender Difference Index (SDI) was developed to quantify gender-based disparities in both temporal and spatial dimensions. Correlation analysis was employed to examine spatial influencing factors and their interrelationships. The results indicate that on holidays, a stable male-dominant usage pattern was observed across all parks, with males showing a preference for cultural parks. On weekdays, although male users remain predominant overall, considerable variations exist among parks. On a daily scale, males exhibit earlier and more flexible activity patterns, whereas females demonstrate significantly lower presence during evening hours, indicating a “nocturnal poverty” phenomenon. Spatially, community parks display the greatest gender disparity, whereas comprehensive parks show relative gender balance. Although both genders value barrier-free facilities, females place additional emphasis on service facilities, while males are more influenced by mixed land-use functions surrounding the parks. This study demonstrates that high-precision, large-coverage multi-source data can accurately and dynamically identify gender-based differences in green space usage and their influencing factors, providing valuable insights for inclusive urban planning.

The compactness, diversity, and nested structures of the old districts in Chinese cities, in terms of their three-dimensional (3D) morphology, are particularly distinctive. However, existing multifractal measurement methods are insufficient in revealing these 3D structures. This paper introduces a 3D multifractal approach based on generalized dimension and Rényi entropy. In particular, a local indicator τ_q(h) is introduced for the analysis of the mapping of 3D units, with the Nanjing Old City serving as a case study. The results indicate the following: (1) The significant fractal characteristics of the Nanjing Old City, with a capacity dimension value of 2.344, indicating its limited 3D spatial occupancy. (2) The fluctuating generalized dimension spectrum ranges from 2.241 to 2.660, which differs from previous studies, suggesting that the 3D morphology does not exhibit typical multifractal characteristics. (3) The 3D map matrix reveals a fragmented open space system, a heterogeneous distribution of high-rise buildings, and cross-scale variations in morphological heterogeneity. This 3D multifractal method aids urban planners in assessing critical issues such as the fragmentation, crowding, and excessive heterogeneity of urban morphology, providing a spatial coordination and scaling of these issues through the 3D map matrix and enhancing the discussion of the broader mechanisms influencing morphological characteristics.