Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion

Abstract Drylands are critical in regulating global carbon sequestration, but the resiliency of these semi‐arid shrub, grassland and forest systems is under threat from global warming and intensifying water stress. We used synergistic satellite optical‐Infrared (IR) and microwave remote sensing observations to quantify plant‐to‐stand level vegetation water potentials and seasonal changes in dryland water stress in the southwestern U.S. Machine‐learning was employed to re‐construct global satellite microwave vegetation optical depth (VOD) retrievals to 500‐m resolution. The re‐constructed results were able to delineate diverse vegetation conditions undetectable from the original 25‐km VOD record, and showed overall favorable correspondence with in situ plant water potential measurements (R from 0.60 to 0.78). The VOD water potential estimates effectively tracked plant water storage changes from hydro‐climate variability over diverse sub‐regions. The re‐constructed VOD record improves satellite capabilities for monitoring the storage and movement of water across the soil‐vegetation‐atmosphere continuum in heterogeneous drylands.

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Publication Details

Journal
Geophysical Research Letters
Published
2024-11-04
DOI
https://doi.org/10.1029/2024gl110385
Citations
5
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
1.03

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article

Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion

John S. Kimball, Jinyang Du, Steven A. Kannenberg, K. Arthur Endsley et al.
5 citations
Geophysical Research Letters
Soil Moisture and Remote Sensing
1.03
article

Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion

John S. Kimball, Jinyang Du, Steven A. Kannenberg, K. Arthur Endsley, Andrew F. Feldman, William K. Smith, Jessica Guo
article en
5 citations

Abstract

Abstract Drylands are critical in regulating global carbon sequestration, but the resiliency of these semi‐arid shrub, grassland and forest systems is under threat from global warming and intensifying water stress. We used synergistic satellite optical‐Infrared (IR) and microwave remote sensing observations to quantify plant‐to‐stand level vegetation water potentials and seasonal changes in dryland water stress in the southwestern U.S. Machine‐learning was employed to re‐construct global satellite microwave vegetation optical depth (VOD) retrievals to 500‐m resolution. The re‐constructed results were able to delineate diverse vegetation conditions undetectable from the original 25‐km VOD record, and showed overall favorable correspondence with in situ plant water potential measurements (R from 0.60 to 0.78). The VOD water potential estimates effectively tracked plant water storage changes from hydro‐climate variability over diverse sub‐regions. The re‐constructed VOD record improves satellite capabilities for monitoring the storage and movement of water across the soil‐vegetation‐atmosphere continuum in heterogeneous drylands.

Geophysical Research LettersVol. 51(21)
West Virginia University (US), Goddard Space Flight Center (US), Harvey Mudd College (US), University of Arizona (US), Earth System Science Interdisciplinary Center (US), University of Maryland, College Park (US), University of Montana (US)
National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, University of Montana, Nuclear Safety and Security Commission, Division of Environmental Biology
Openalex Percentile: Top 26%
Soil Moisture and Remote Sensing
1.03
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