Bayesian spatio-temporal models for mapping urban pedestrian traffic
Bibliographic Data
| ID | 12296378 |
|---|---|
| Authors | Mounia Zaouche (University of Bristol, corresponding author), Nikolai W F Bode (0000-0003-0958-5191, University of Bristol, corresponding author) |
| Year | 2023 |
| Volume | 111 |
| Pages | 103647-103647 |
| Publication date | 2023-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Transport Geography (JOURNAL) |
| Journal identifiers | ISSN: 0966-6923 • E-ISSN: 1873-1236 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jtrangeo.2023.103647 |
| OpenAlex | W4385164127 |
| Language | EN |
| Citations received | 3 |
| References cited | 40 |
Bayesian inference · Bayesian probability · Data mining · Inference · Laplace's method · Pedestrian · Street network · Transport engineering · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Traffic Prediction and Management Techniques · Urban Transport and Accessibility · Artificial Intelligence
Spatial and Spatio‐temporal Bayesian Models with R‐Inla
Multidimensional Scaling
An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields
Configurational Modelling of Urban Movement Networks
Bayesian Spatial Modelling with R - Inla
The Kolmogorov-Smirnov Test for Goodness of Fit
Ggplot2
Bayesian Measures of Model Complexity and Fit
Estimating Pedestrian Flows on Street Networks
Connecting the city
Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows
Spatiotemporal exploration of Melbourne pedestrian demand
Circuity in urban transit networks
Spatial prediction of traffic levels in unmeasured locations
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |