Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 17, issue 9
Articles | Volume 17, issue 9
https://doi.org/10.5194/amt-17-3029-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-17-3029-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 9
Research article
 | 
17 May 2024
Research article |  | 17 May 2024

Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation

Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom

Viewed

Total article views: 1,466 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,059 347 60 1,466 58 54
  • HTML: 1,059
  • PDF: 347
  • XML: 60
  • Total: 1,466
  • BibTeX: 58
  • EndNote: 54
Views and downloads (calculated since 02 May 2023)
Cumulative views and downloads (calculated since 02 May 2023)

Viewed (geographical distribution)

Total article views: 1,466 (including HTML, PDF, and XML) Thereof 1,430 with geography defined and 36 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
Short summary
The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency and resolution and can be used in real time, which is valuable for aviation, forecasting, and air quality monitoring.
Read more
Special issue
Profiling the atmospheric boundary layer at a European scale...