Difference between revisions of "IS428 AY2018-19T1 Kim Do Yeon"

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== References ==
 
== References ==
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*Meteological factors -Article(https://www.qld.gov.au/environment/pollution/monitoring/air/air-monitoring/meteorology-influence/meteorology-factors)
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*Tableau-Density heatmap(https://onlinehelp.tableau.com/current/pro/desktop/en-us/buildexamples_density.htm)
  
 
== Comments ==
 
== Comments ==

Revision as of 21:35, 11 November 2018

Problem & Motivation

Air quality in Bulgaria is now a big concern. The Air quality has been measured every day to keep track of and detect whether the air in Bulgaria is detrimental to people’s health. According to the World Health Organisation, Bulgaria had the highest PM2.5 concentrations of all EU -28-member states in urban areas over the three years average. For PM10, Bulgaria is one of the top countries with 77 micrograms per cube metre (EU limit is 50 micrograms per cube metre). With the large sets of data collected from the sensor, the PM 10 air quality and its factors can be measured. Here, data visualisation will aid in finding the patterns of air quality in Sofia city as well as to identify the issues and factors of air pollution. The interactive visualisation has three functions

  • 1) Patterns of air quality in Sofia city from 2013 to 2018 on a daily and hourly basis
  • 2) Showing the pattern of the data (Temperature, Humidity, Pressure) collected from the sensor.
  • 3) Compare the air pressure and meteorology of Sofia City. Reveal the relationships between the factors causing air quality in Sofia City

Visualisation 1( Spatio-temporal Analysis of Official Air Quality)

  • Data Preparation

For the task, 4 major data sets were in zipped file format and were provided and for visualisation 1, EEA Data.zip was used. First zipped file (EEA Data.zip) had official air quality measurements from 2013 to 2018 from 5 different regions. Before using all the data, some of the files were not included in the visualisation.


Visualisation 2 ( Spatio-temporal Analysis of Citizen Science Air Quality Measurements)

  • Data preparation

In Air tube zip file, there are two csv files. Sensors recorded temperature, humidity and pressure from 2017 to 2018. The Geohash is converted to longitude and latitude using R code(geohash library and “gh_decode()” function was used).After converting the geohash to longitude and latitude, the data frame of 2017,2018 were merged and its respective longitude and latitude were concatenated.

Visualisation 3 (Factors affecting the air quality of the city)

  • Data preparation

From Meteorological Data readings, we can get the latitude and the longitude of the Sofia Airport

  • Latitude: 42.6537
  • Longitude: 23.3829
  • Elevation: 595 m


References

Comments