Cycling accidents in Guadalajara, Mexico

**Dataset Description** This repository provides a high-resolution, geospatial, segment-level dataset linking 774 cyclist-involved crashes (2015–2024) in the Guadalajara Metropolitan Area (Mexico) to a uniformly segmented cycling network. The dataset was created to facilitate research on cyclist safety, infrastructure planning, and policy evaluation by providing a pre-processed, analysis-ready resource that eliminates the need for extensive geocoding and data integration. ### **Key Features** * **High-Resolution Network:** The cycling network is systematically divided into approximately 13,380 micro-segments of ~20 meters each. * **Crash-Segment Linkage:** Each of the 774 crash records is spatially joined to a unique segment identifier (`IDSegmento`). Crashes occurring off the formal network are assigned `IDSegmento = 0`. * **Derived Analytical Variables:** Includes key variables for spatial analysis, such as: * `Concentracion_accidentes`: The total count of crashes occurring on the same segment, ideal for hotspot detection. * `Riesgo`: A derived qualitative indicator ('red', 'yellow', 'green') based on the frequency of recent accidents. * **Full Reproducibility:** The dataset is accompanied by comprehensive, machine-readable metadata, including schemas, codebooks, checksums, and the full data generation pipeline script. ### **Data Content** The main data files are provided in CSV format (`utf-8-sig` encoded for Excel compatibility): 1. **`accidentes_idsegmento_frecuencia.csv`**: The primary dataset of 774 person-level crash records. 2. **`segmentos_ciclovias.csv`**: The segmented cycling network layer. ### **Potential Use Cases** This structure facilitates fine-grained spatial analysis, hotspot detection, and predictive model training. The documented workflow can also be replicated to create similar datasets for other Latin American cities under similar data conditions, enabling valuable comparative research. This dataset supports the *Data in Brief* article: "A High-Resolution Geospatial Dataset of Cyclist-Involved Crashes and Segmented Cycling Infrastructure in the Guadalajara Metropolitan Area (2015–2024)".