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 obse...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2024GL110385 |
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| author | J. Du J. S. Kimball J. S. Guo S. A. Kannenberg W. K. Smith A. Feldman A. Endsley |
| author_facet | J. Du J. S. Kimball J. S. Guo S. A. Kannenberg W. K. Smith A. Feldman A. Endsley |
| author_sort | J. Du |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-009d9d1fed3a4d9d8ae6bdb2e38af2e4 |
| institution | DOAJ |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-009d9d1fed3a4d9d8ae6bdb2e38af2e42025-08-20T03:02:07ZengWileyGeophysical Research Letters0094-82761944-80072024-11-015121n/an/a10.1029/2024GL110385Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor FusionJ. Du0J. S. Kimball1J. S. Guo2S. A. Kannenberg3W. K. Smith4A. Feldman5A. Endsley6Numerical Terradynamic Simulation Group University of Montana Missoula MT USANumerical Terradynamic Simulation Group University of Montana Missoula MT USAHixon Center for Climate and the Environment & Biology Department Harvey Mudd College Claremont CA USADepartment of Biology West Virginia University Morgantown WV USASchool of Natural Resources and the Environment University of Arizona Tucson AZ USABiospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt MD USANumerical Terradynamic Simulation Group University of Montana Missoula MT USAAbstract 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.https://doi.org/10.1029/2024GL110385VODsatellitemachine learningvegetation water potential |
| spellingShingle | J. Du J. S. Kimball J. S. Guo S. A. Kannenberg W. K. Smith A. Feldman A. Endsley Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion Geophysical Research Letters VOD satellite machine learning vegetation water potential |
| title | Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion |
| title_full | Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion |
| title_fullStr | Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion |
| title_full_unstemmed | Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion |
| title_short | Enhanced Satellite Monitoring of Dryland Vegetation Water Potential Through Multi‐Source Sensor Fusion |
| title_sort | enhanced satellite monitoring of dryland vegetation water potential through multi source sensor fusion |
| topic | VOD satellite machine learning vegetation water potential |
| url | https://doi.org/10.1029/2024GL110385 |
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