Abstract
Air pollution in big cities is a major health problem. Pollutants in the air may have severe consequences in humans, creating conditions for several illness and also affect tissues and organs, and also affect other animals and crop productivity. From several years now, the air quality has been monitored by stations distributed over major cities, and the concentration of several pollutants is measured. From these data sets, and applying the data visualization capabilities of the self-organized map, we analyzed the air quality in Mexico City. We were able to detect some hidden patterns regarding the pollutant concentration, as well as to study the evolution of air quality from 2003 to 2010.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Sportisse, B.: Fundamentals in air pollution. Springer, Heidelberg (2010)
Seinfeld, J., Pandis, S.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 2nd edn. Wiler (2006)
Knox, E.: Atmospheric pollutants and mortalities in English local authority areas. J Epidemiol Community Health 62, 442–447 (2008)
Ferrer-Carbonell, J., Escalante-Semerena, R.: Contaminación atmosférica y efectos sobre la salud en la Zona Metropolitana del Valle de México. Revista Economía Informa 360, 119–143 (2008)
Bell, M., Davis, D., Guoveia, N., Borja, V., Cifuentes, L.: The avoidable health effects of air pollution in three Latin American cities: Santiago, São Paulo and Mexico City. Environmental Research 100, 431–440 (2006)
Kohonen, T.: Self-Organizing maps, 3rd edn. Springer, Heidelberg (2000)
Hujun, Y.: The self-organizing maps: Background, theories, extensions and applications. In: Computational Intelligence: A Compendium, pp. 715–762 (2008)
Kaski, S., Kohonen, T.: Exploratory data analysis by the self-organizing map: structures of welfare and poverty in the world. In: Apostolos-Paul, N.R. (ed.) Neural Nwteorks in Financial Engineering, pp. 498–507 (1996)
Ultsch, A.: Self organizied feature maps for monitoring and knowledge aquisition of a chemical process. In: Proc. of the Int. Conf. on Artificial Neural Networks, pp. 864–867 (1993)
Alvarez-Guerra, E.: A SOM-based methodology for classifying air quality monitoring stations (2010), doi:10.1002/ep.10474
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Neme, A., Hernández, L. (2011). Visualizing Patterns in the Air Quality in Mexico City with Self-Organizing Maps. In: Laaksonen, J., Honkela, T. (eds) Advances in Self-Organizing Maps. WSOM 2011. Lecture Notes in Computer Science, vol 6731. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21566-7_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-21566-7_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21565-0
Online ISBN: 978-3-642-21566-7
eBook Packages: Computer ScienceComputer Science (R0)