M
María Henar Salas-Olmedo
Researcher at Complutense University of Madrid
Publications - 20
Citations - 1004
María Henar Salas-Olmedo is an academic researcher from Complutense University of Madrid. The author has contributed to research in topics: Big data & Metropolitan area. The author has an hindex of 11, co-authored 20 publications receiving 777 citations. Previous affiliations of María Henar Salas-Olmedo include University of Cantabria.
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The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona
TL;DR: Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the city's main hotel axis and hotels predominate in some peripheral areas of the city.
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Tourists' digital footprint in cities: Comparing Big Data sources
TL;DR: The main conclusion is that it is not sufficient to use one data source to analyse the presence of tourists in cities; several must be used in a complementary manner.
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City dynamics through Twitter: Relationships between land use and spatiotemporal demographics
Juan Carlos García-Palomares,María Henar Salas-Olmedo,Borja Moya-Gómez,Ana Condeço-Melhorado,Javier Gutiérrez +4 more
TL;DR: In this paper, the authors used Twitter data to analyse city dynamics over the course of the day and found that the influence of different land uses on each of the major time slots (morning, afternoon, evening and night) through their changing coefficients.
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Dynamic Accessibility using Big Data: The Role of the Changing Conditions of Network Congestion and Destination Attractiveness
TL;DR: This paper analyzes urban accessibility considering its two components –the performance of the transport network and the attractiveness of the destinations– using a dynamic approach using data from TomTom and Twitter respectively, to obtain profiles that highlight the daily variations in accessibility in the city of Madrid.
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Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis
TL;DR: A dynamic analysis of urban accessibility considering its two main components: travel times and the attractiveness of destinations is conducted, indicating that these new sources of geolocated data show considerable potential for use in time-sensitive accessibility studies, since they yield more accurate and realistic information than static or partially dynamic analyses.