Accessibility settings

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58761, first published .
Flowchart of a human-machine adversarial scoring framework for street-view images and bike-sharing orders in Shanghai.

Moderation Effects of Streetscape Perceptions on the Associations Between Accessibility, Land Use Mix, and Bike-Sharing Use: Cross-Sectional Study

Moderation Effects of Streetscape Perceptions on the Associations Between Accessibility, Land Use Mix, and Bike-Sharing Use: Cross-Sectional Study

Journals

  1. Guo H, Li Y, Liu Y, Zhang S, Zhang Y, Ho H. Can good neighbourhood perception magnify the positive effect of favourable built environment on recreational walking in China?. BMC Public Health 2024;24(1) View
  2. Wang Y, Cui T, Zhong W, Ma Y, Shi C, Liu W, Hu Q, Zhang B, Zhang Y, Liu H. Study on Accessibility and Equity of Park Green Spaces in Zhengzhou. ISPRS International Journal of Geo-Information 2025;14(10):392 View
  3. Wu H, Zhu L, Chen Q, Deng H. An Explainable Machine Learning Framework Based on XGBoost-SHAP and Multi-Source Geospatial Data: Systematic Analysis of Urban Vitality and Influencing Factors in Changsha. Systems 2026;14(7):842 View
  4. Chen J, Lin Y, Yu J, Du J, Liu P. Exploring the determinants of hydrogen bike-sharing adoption among urban residents using explainable machine learning. Transportation Research Part A: Policy and Practice 2026;212:105174 View