Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements
Data Preparation
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Illustration
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- First of all, there are two data sets, one for 2017 and the other for 2018, provided for spatio-temporal analysis of citizen science air quality.
- In each data set, the sensors are captured by the geohash code. After acquiring the longitude and latitude by using R programming, we are able to draw the density geographic maps on P1 or P2 showed by the following pictures.
- In this task, I would prefer to do the analysis by separately going through the two data sets because it was noticed that the number of sensors included in each data sets are different and cannot be joined effectively during my initial exploration on the two data sets. In order to get the clearer whole picture on the air quality, it is better to take care of them separately.
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Characterize the Sensors’ Coverage, Performance and Operation
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Dashboard Visualization
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Coverage
Sensors are not only distributed over the Sofia City
- By taking advantage of Sofia topography data set, we are able to distinguish whether the geographic location of the sensors included in the data set are all in the Sofia City.
- From the view of the group of maps in the dashboard showed below, both the Original Sensors Coverage Maps in 2017 and 2018 are located over the Bulgaria country rather than only for the Sofia City. Hence, we need to filter out the geohash codes that are out of Sofia City by referring to the sofia_topo dataset which includes Sofia urban area and some areas nominally external to the city (toward Vitosha mountain, note large elevation numbers), although it has no particular effort to include entirety of Sofia Capital's area as per administrative boundaries.
- In the view of the whole Bulgaria country, there are major three areas that have higher concentration on P1 or P2 in these two years and Sofia city is the most serious polluted city in Bulgaria with a larger intense cycle on the deeper blue colour. The other finding is that by comparing the two Original Sensors Coverage Maps in 2017 and 2018, it is easily to notice that there are more sensors captured in 2018 than in 2017 based on the larger number of data points plotted on the maps. Besides, by comparing the two Sensors in Sofia maps in 2017 and 2018, the points are more intense in 2018 than in 2017 which illustrate a situation that the pollution is more series in 2018.
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Example
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Example
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