Information-based uncertainty decomposition in dual-channel microwave remote sensing of soil moisture

Li, Bonan; Good, Stephen P.

doi:https://doi.org/10.5194/hess-25-5029-2021

Articles | Volume 25, issue 9

https://doi.org/10.5194/hess-25-5029-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-5029-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 9

Research article

|

17 Sep 2021

Research article |

| 17 Sep 2021

Information-based uncertainty decomposition in dual-channel microwave remote sensing of soil moisture

Bonan Li and Stephen P. Good

Supplement

https://doi.org/10.5194/hess-25-5029-2021-supplement

Data sets

SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture P. E. O'Neill, S. Chan, E. G. Njoku, T. Jackson, R. Bindlish, and J. Chaubell https://doi.org/10.5067/F1TZ0CBN1F5N

In situ soil moisture NOAA https://www.ncdc.noaa.gov/crn/qcdatasets.html

MCD15A3H MODIS/Terra+Aqua Leaf Area Index/FPAR 4-day L4 Global 500 m SIN Grid V006 R. Myneni, Y. Knyazikhin, and T. Park https://doi.org/10.5067/MODIS/MCD15A3H.006

Model code and software

Information-based uncertainty decomposition of remote sensing of soil moisture B. Li https://doi.org/10.5281/zenodo.5508246

Short summary

We found that satellite retrieved soil moisture has large uncertainty, with uncertainty caused by the algorithm being closely related to the satellite soil moisture quality. The information provided by the two main inputs is mainly redundant. Such redundant components and synergy components provided by two main inputs to the satellite soil moisture are related to how the satellite algorithm performs. The satellite remote sensing algorithms may be improved by performing such analysis.