Publication: Madrid, isla de calor
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2023-02
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Abstract
Madrid como tantas otras ciudades, es una ” isla de calor ”. El calentamiento del asfalto y de los edificios hacen que la temperatura suba en unas zonas más que en otras, algo que podemos comprobar cuando nos movemos entre diferentes distritos de la ciudad.
En este trabajo se pretende estudiar las relaciones entre los distintos contaminantes, la meteorología y las zonas verdes e hidrográficas, empleando datos históricos recogidos por las estaciones que se encuentran por la ciudad de Madrid. Aplicando algoritmos de Machine Learning podremos determinar si esta correlación afecta en las temperaturas de las distintas zonas de la ciudad.
Madrid, like so many other cities, is a ”heat island”. The heating of the asphalt and buildings makes the temperature rise in some areas more than in others, something that we can see when we move between different districts of the city. The aim of this work is to study the relationships between different pollutants, meteorology and green areas and hydrographic zones, using historical data collected by the stations located in the city of Madrid. By applying Machine Learning algorithms we will be able to determine if this correlation affects the temperatures of the different areas of the city.
Madrid, like so many other cities, is a ”heat island”. The heating of the asphalt and buildings makes the temperature rise in some areas more than in others, something that we can see when we move between different districts of the city. The aim of this work is to study the relationships between different pollutants, meteorology and green areas and hydrographic zones, using historical data collected by the stations located in the city of Madrid. By applying Machine Learning algorithms we will be able to determine if this correlation affects the temperatures of the different areas of the city.
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Trabajo de Fin de Grado en Ingeniería Informática e
Ingeniería del Software, Facultad de Informática UCM, Departamento de Sistemas Informáticos y Computación, Curso 2022/2023.