Dual-Dimensional Walkability Data for 82 Chinese Cities: Street, Neighborhood, and Individual Scales

This dataset provides walkability metrics across three spatial scales for 82 Chinese cities. 📂 Data Structure 1. Street-Level Walkability (street-level walkability/) Item Description Files {city_name}_streets.json (82 files) Contents Static Walkability Index (SWI) and daily-averaged Dynamic Walkability Index (DWI) for each street segment in the urban road network 2. Neighborhood-Level Walkability (neighborhood-level walkability/) Item Description Files {city_name}_neighborhoods.json (82 files) Contents Aggregated SWI and daily-averaged DWI for neighborhoods aggregated by 0.005° × 0.005° grid cells 3. Individual-Level Experience (individual-level experience/) Source data for figures in the main text: File Column 1 Other Columns Figure 1j-l.csv city_name PE_SWI, PE_DWI Figure 3a (all cities).csv Home_SWI City-specific PE_SWI Figure 3b (all cities).csv Home_SWI City-specific PE_DWI Figure 3c (all cities).csv Home_DWI City-specific PE_DWI Figure 3d (all cities).csv Home_DWI City-specific PE_SWI 📖 Key Definitions Term Definition SWI (Static Walkability Index) Built environment quality DWI (Dynamic Walkability Index) Traffic exposure derived from mobility data PE (Pedestrian Experience) Time-weighted walkability experienced along actual walking routes Home Index Walkability of an individual's residential neighborhood (15-minute catchment)