Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 24th Iberoamerican Congress, CIARP 2019, Proceedings |
| Editors | Ingela Nyström, Yanio Hernández Heredia, Vladimir Milián Núñez |
| Publisher | Springer |
| Pages | 514-524 |
| Number of pages | 11 |
| ISBN (Print) | 9783030339036 |
| DOIs | |
| State | Published - 2019 |
| Event | 24th Iberoamerican Congress on Pattern Recognition, CIARP 2019 - Havana, Cuba Duration: 28 Oct 2019 → 31 Oct 2019 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11896 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 24th Iberoamerican Congress on Pattern Recognition, CIARP 2019 |
|---|---|
| Country/Territory | Cuba |
| City | Havana |
| Period | 28/10/19 → 31/10/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Forecasting
- Operational dynamics
- Smart cities
- Time series
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