2026-07-30T22:54:02Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/68642024-05-20T09:51:34Zcom_10259.4_104com_10259_2604col_10259_6848

Romanillos Arroyo, Gustavo García Palomares, Juan Carlos Moya-Gómez, Borja Gutiérrez Puebla, Javier Torres, Javier López, Mario García Cantú Ros, Oliva Herranz, Ricardo 2022-09-15T11:25:56Z 2022-09-15T11:25:56Z 2021-07 978-84-18465-12-3 http://hdl.handle.net/10259/6864 10.36443/10259/6864 Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos Because of the fast expansion of the COVID-19 pandemic in 2020, many countries established lockdowns, implementing different restrictions on people’s mobility. Analysing the effectiveness of these measures is crucial to better react to similar future scenarios. This research uses anonymous mobile phone data to study the impact of the Spanish lockdown on the daily dynamics of the Madrid metropolitan area. The analysis is focused on a reference week prior to the lockdown and on several weeks of the lockdown in which different restrictions were in place. For this timeframe, population distribution is compared during the day and at night and presence profiles are obtained throughout the day for each type of land use. In addition, a multiple regression analysis is carried out to determine the impact of the different land uses on the local population. The results in the reference week, pre-COVID-19, show how the population in activity areas increases in each time slot on a specific day and how in residential areas it decreases. However, during the lockdown, activity areas cease to attract population during the day and the residential areas therefore no longer show a decrease. Only basic essential commercial activities, or others that require the presence of workers maintain some activity during lockdown. This research was financed by the Spanish The Ministry of Science, Innovation and Universities through the project “DynMobility - Análisis dinámico de los patrones de movilidad a partir del Big Data” (code RTI2018-098402-B-I00), and also supported by the Madrid Region authority through the Research Network “INNJOBMAD-CM - Atracción de actividades económicas innovadoras y creadoras de trabajo en Madrid.” application/pdf eng Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional R-Evolucionando el transporte http://hdl.handle.net/10259/6490 https://doi.org/10.36443/9788418465123 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098402-B-I00/ES/ANALISIS DINAMICO DE LOS PATRONES DE MOVILIDAD A PARTIR DE BIG DATA COVID-19 Ingeniería civil Transportes Civil engineering Transportation Urban population dynamics during the COVID- 19 pandemic based on mobile phone data info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/openAccess 279 293