Inclusive Mobility in Chiang Mai
Description
This dataset provides a per-second table that combines pedestrian GPS trajectories with synchronized streetscape “micro-barrier” counts for Old City area of Chiang Mai, Thailand. Each row represents one second along a fixed itinerary walked or wheeled by study participants. The data were collected to analyse inclusive mobility, in particular, differences between walking and manual wheelchair users in a heritage, tourism-intensive environment. File and structure. “inclusive_mobility.csv” Columns: timestamp (ISO 8601, UTC), mode (walk/wheelchair), occasion (morning/afternoon/evening), lon, lat (WGS84, EPSG:4326), speed_kmh (instantaneous speed), and second-level barrier counts: persons_s, cars_s, motorcycles_s. Barrier counts are the sum of detections across 30 frames within each second. Timestamps are aligned exactly at 1-second resolution so that movement and context are directly comparable. Coverage and quality: The time span covers multiple passes along the Old City route across different times of day (tourism corridors linking temples/landmarks). Coordinates fall within the Old City bounding box. The table contains no personally identifiable information; trajectories are anonymized. Per-second speed values reflect mixed pedestrian conditions (stop-and-go near obstacles/crossings). As with consumer GPS, small positional jitter is possible near buildings/trees; brief speed spikes may occur where satellite geometry is poor. No map-matching or smoothing is applied in this file unless noted. Intended use: Transport geography and urban planning analyses of speed dynamics, route geometry, and mobility inequality; reproducible modelling (e.g., Bayesian state-space) linking behaviour to micro-barriers; teaching materials for R/Stan workflows. Researchers may divide persons, crass, or motorcyclists by ~30 to obtain approximate per-frame averages, or aggregate by segment/time window for modelling. Ethics and privacy: No face data or re-identification is included. Barrier variables are object categories only. Please consult the associated article for ethics/IRB notes. Citation and versioning. Cite the Mendeley Data DOI for this dataset (include version), and the Zenodo DOI for the archived code release that reproduces the analysis. Use a permissive license (e.g., CC BY 4.0) to enable reuse.