Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals
Name
Error_Propagation_in_Microwave_Soil_Moisture_and_Vegetation_Optical_Depth_Retrievals.pdf
Description
Published version
Size
2.4 MB
Format
Adobe PDF
Checksum (MD5)
160539109ef59476e54162ae59ccf594
Author(s)
Feldman, Andrew
Chaparro, David
Entekhabi, Dara
Date Issued
2021
Journal
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Feldman, Andrew, Chaparro, David and Entekhabi, Dara. 2021. "Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals." Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 14.
Version
Final published version
Abstract
Satellite soil moisture and vegetation optical depth [(VOD); related to the total vegetation water mass per unit area] are increasingly being used to study water relations in the soil-plant continuum across the globe. However, soil moisture and VOD are typically jointly estimated, where errors in the optimization approach can cause compensation between both variables and confound such studies. It is thus critical to quantify how satellite microwave measurement errors propagate into soil moisture and VOD. Such a study is especially important for VOD given limited investigations of whether VOD reflects in situ plant physiology. Furthermore, despite new approaches that constrain (or regularize) VOD dynamics to reduce soil moisture errors, there is limited study of whether regularization reduces VOD errors without obscuring true vegetation temporal dynamics. Here, we find that, across the globe, VOD is less robust to measurement error (more difficult for optimization methods to find the true solution) than soil moisture in their joint estimation. However, a moderate degree of regularization (via time-constrained VOD) reduces errors in VOD to a greater degree than soil moisture and reduces spurious soil moisture-VOD coupling. Furthermore, despite constraining VOD time dynamics, regularized VOD variations on subweekly scales are both closer to simulated true VOD time series and have global VOD post-rainfall responses with reduced error signatures compared to VOD retrievals without regularization. Ultimately, we recommend moderately regularized VOD for use in large scale studies of soil-plant water relations because it suppresses noise and spurious soil moisture-VOD coupling without removing the physical signal.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/JSTARS.2021.3124857
