Advances in Science and Research
Advances in Science and Research
ASR
Articles | Volume 18
Articles | Volume 18
https://doi.org/10.5194/asr-18-65-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/asr-18-65-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18
11 May 2021
 | 11 May 2021

Using machine learning to produce a very high resolution land-cover map for Ireland

Eoin Walsh, Geoffrey Bessardon, Emily Gleeson, and Priit Ulmas

Viewed

Total article views: 5,182 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,712 436 34 5,182 42 37
  • HTML: 4,712
  • PDF: 436
  • XML: 34
  • Total: 5,182
  • BibTeX: 42
  • EndNote: 37
Views and downloads (calculated since 11 May 2021)
Cumulative views and downloads (calculated since 11 May 2021)

Viewed (geographical distribution)

Total article views: 4,890 (including HTML, PDF, and XML) Thereof 4,890 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 07 Dec 2023
Download
Short summary
In this work, machine learning techniques, satellite data and land-cover data were used to produce a land-cover map for Ireland that shows greater accuracy and resolution than an altered version of the standard land-cover map (ECOCLIMAP-SG) used for numerical weather prediction. This method offers a way to universally improve meteorological land-cover maps across jurisdictions, while also offering a method of updating the map regularly to account for seasonal changes in surface land-covers.
Read more