Difference between revisions of "ISSS608 2018-19 T1 Assign Qiao Xueyu Visualization"
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− | [[File:Citizen | + | [[File:Citizen co.png|600px|frameless|left]] |
|| The Coverage Map shows the citizen sensors' coverage.<br> | || The Coverage Map shows the citizen sensors' coverage.<br> | ||
− | * The color of circles shows the percentage of anomalies with red indicating high percentage of anomalies <br> | + | * The color of circles shows the a percentage of anomalies with red indicating high percentage of anomalies <br> |
* The size of circles shows the number of measure records <br> | * The size of circles shows the number of measure records <br> | ||
* Click from the Anomalies list to select the well-operated or badly-operated sensors <br> | * Click from the Anomalies list to select the well-operated or badly-operated sensors <br> | ||
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* Click the play button to play the animation <br> | * Click the play button to play the animation <br> | ||
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== Air Quality & Other Factors == | == Air Quality & Other Factors == | ||
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Revision as of 11:33, 18 November 2018
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View the interactive dashboard here
Official Air Quality Measurements
The Map shows the distribution of official stations.
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The Hourly Trend graph shows the average hourly PM10 concentration of each station.
Parameter created:
Calculation Fields created:
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The Overall Trend graph shows the trend of each station according to the date granularity selected.
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Citizen Science Air Quality Measurements
The Coverage Map shows the citizen sensors' coverage.
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The Anomalies graph shows the number of anomalies and the percentage of anomalies over the time period.
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The PM10 & PM2.5 Heatmap shows the concentration change over the time period.
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Air Quality & Other Factors
The graph on the left helps us to explore the relationship between PM10 concentration and attributes of them like distance to curb, distance to building and altitude.
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The line charts of meteorological variables help us explore the relationship between meteorological factors and pollutant concentration. |