de las Obras-Loscertales, JuliaGarcía Palomares, Juan CarlosRamiro-Fariñas, DiegoHernández Martín-Caro, María SoledadGutiérrez Puebla, Javier2026-03-022026-03-022026-02-27de las Obras-Loscertales, J., García-Palomares, J.C., Ramiro-Fariñas, D., Hernández Martín-Caro, M.ªS., & Gutiérrez, J. (2026). Temporal and spatial distribution of spending in the city using bank cards transactions. Boletín de la Asociación de Geógrafos Españoles,(108). https://doi.org/10.21138/bage.370410.21138/bage.3704https://hdl.handle.net/20.500.14352/133671Despite the economic, social, and symbolic importance of urban consumption, its study has been constrained by the lack of sources with sufficient spatial and temporal resolution until the emergence of new Big Data sources. However, most studies rely on static analyses, limiting spatiotemporal understanding. Using bank card transactions, this study examines the temporal, spatial, and spatiotemporal distribution of consumption in the city of Madrid, by consumer type and commercial sector. Likewise, through the use of time series clustering techniques and Sequence Alignment Analysis, different types of consumption spaces have been identified according to the daily spending patterns and the sequence of the predominant commercial sectors, respectively. The results reveal different hourly distributions by the day of the week, as well as varying spatial distributions by sector, consumer type, and time of day. By jointly analysing temporal rhythms and sectoral sequences, the study moves beyond conventional classifications of urban commercial areas, allowing the definition of spatial typologies that highlight of consumption peaks, the predominant commercial sector at different times, and behaviour during the night and weekends are of great importance in characterising these spaces. The study demonstrates that analysing bank card transaction data and incorporating a spatiotemporal approach provides insights for urban managers and planners.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal articlehttps://bage.age-geografia.es/ojs/index.php/bage/article/view/3704/1111113249open access911.3:33consumptionBig Dataspatiotemporal patternsMadridGeografíaGeografía humanaGeografía económica2505 Geografía