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

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

doi:https://doi.org/10.5194/bg-19-5107-2022

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:

Microwave remote sensing for improved understanding of vegetation–water...

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

Data sets

The Standardized Vegetation Optical Depth Index SVODI Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo https://doi.org/10.5281/zenodo.7114654

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.