Geoscientific Instrumentation, Methods and Data Systems
Geoscientific Instrumentation, Methods and Data Systems
GI
Articles | Volume 10, issue 2
Articles | Volume 10, issue 2
https://doi.org/10.5194/gi-10-265-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-10-265-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 2
Research article
 | 
03 Nov 2021
Research article |  | 03 Nov 2021

Evaluation of multivariate time series clustering for imputation of air pollution data

Wedad Alahamade, Iain Lake, Claire E. Reeves, and Beatriz De La Iglesia

Viewed

Total article views: 3,014 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,184 751 79 3,014 62 46
  • HTML: 2,184
  • PDF: 751
  • XML: 79
  • Total: 3,014
  • BibTeX: 62
  • EndNote: 46
Views and downloads (calculated since 17 May 2021)
Cumulative views and downloads (calculated since 17 May 2021)

Viewed (geographical distribution)

Total article views: 3,014 (including HTML, PDF, and XML) Thereof 2,805 with geography defined and 209 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
The goal is to reduce the uncertainty in air quality assessment by imputing all missing pollutants in monitoring stations and identify where more measurements can be beneficial. The proposed approach is based on spatial or temporal similarity between stations. Our proposed approach enables us to impute and estimate plausible concentrations of multiple pollutants at stations across the UK, and the modelled concentrations from the selected models correlated well with the observed concentrations.
Read more