TY - GEN
T1 - A Spatiotemporal Analysis of Taxis Demand
T2 - 24th Iberoamerican Congress on Pattern Recognition, CIARP 2019
AU - Giraldo-Forero, Andres Felipe
AU - Garcia-Lopez, Sebastian
AU - Rodriguez-Marin, Paula Andrea
AU - Martinez, Juan
AU - Céspedes-Villar, Yohan Ricardo
AU - Cardona, Oscar
AU - Acosta, Juan Camilo
AU - Trujillo, Luis Carlos
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - The analysis of urban dynamics has taken on a fundamental role in recent years, even more so considering the accelerated population growth of cities throughout the world. Within this dynamic, one of the most important tasks is urban planning, being able for example to give solution to important problems such as the flow of transport for the improvement of citizen welfare. The following study will present a spatiotemporal analysis of demand flow in taxi service requests in the city of Manizales - Colombia during the year 2016. The study carries out three types of analysis: a spatial analysis that exposes the behavior of requests for taxis throughout the communes of the city, then a temporal analysis is conducted to show the hours of greatest demand and finally the spatiotemporal analysis that gives a general forecast regarding the behavior of taxi requests comprising the second quarter of 2016.
AB - The analysis of urban dynamics has taken on a fundamental role in recent years, even more so considering the accelerated population growth of cities throughout the world. Within this dynamic, one of the most important tasks is urban planning, being able for example to give solution to important problems such as the flow of transport for the improvement of citizen welfare. The following study will present a spatiotemporal analysis of demand flow in taxi service requests in the city of Manizales - Colombia during the year 2016. The study carries out three types of analysis: a spatial analysis that exposes the behavior of requests for taxis throughout the communes of the city, then a temporal analysis is conducted to show the hours of greatest demand and finally the spatiotemporal analysis that gives a general forecast regarding the behavior of taxi requests comprising the second quarter of 2016.
KW - Forecasting
KW - Operational dynamics
KW - Smart cities
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=85075693420&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-33904-3_48
DO - 10.1007/978-3-030-33904-3_48
M3 - Conference contribution
AN - SCOPUS:85075693420
SN - 9783030339036
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 514
EP - 524
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 24th Iberoamerican Congress, CIARP 2019, Proceedings
A2 - Nyström, Ingela
A2 - Hernández Heredia, Yanio
A2 - Milián Núñez, Vladimir
PB - Springer
Y2 - 28 October 2019 through 31 October 2019
ER -
