RT journal article
T1 Land-use dynamic discovery based on heterogeneous mobility sources
A1 Terroso-Saenz, Fernando
A1 Muñoz Ortega, Andrés
A1 Arcas, Francisco
A2 Ingeniería Informática
K1 land labelling
K1 online social networks
K1 supervised learning
K1 urban computing
K1 urban mobility
AB Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transportnetwork connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates.
PB Wiley
SN 0884-8173
YR 2021
FD 2021
LK http://hdl.handle.net/10498/36949
UL http://hdl.handle.net/10498/36949
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-nov-2026