Biogeosciences
Biogeosciences
BG
Articles | Volume 19, issue 21
Articles | Volume 19, issue 21
https://doi.org/10.5194/bg-19-5107-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-19-5107-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 21
Research article
 | 
07 Nov 2022
Research article |  | 07 Nov 2022

Monitoring vegetation condition using microwave remote sensing: the standardized vegetation optical depth index (SVODI)

Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo

Viewed

Total article views: 3,927 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,206 661 60 3,927 41 36
  • HTML: 3,206
  • PDF: 661
  • XML: 60
  • Total: 3,927
  • BibTeX: 41
  • EndNote: 36
Views and downloads (calculated since 21 Jan 2022)
Cumulative views and downloads (calculated since 21 Jan 2022)

Viewed (geographical distribution)

Total article views: 3,927 (including HTML, PDF, and XML) Thereof 3,988 with geography defined and -61 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
Download
Short summary
The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Read more
Special issue
Microwave remote sensing for improved understanding of vegetation–water...
Altmetrics
Final-revised paper
Preprint