Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published March 28, 2024 | Published
Journal Article Open

Investigating Diurnal and Seasonal Cycles of Vegetation Optical Depth Retrieved From GNSS Signals in a Broadleaf Forest

Abstract

Vegetation Optical Depth (VOD) has emerged as a valuable metric to quantify water stress on vegetation's carbon uptake from a remote sensing perspective. However, existing spaceborne microwave remote sensing platforms face limitations in capturing the diurnal VOD variations and global products lack site‐level validation against plant physiology. To address these challenges, we leveraged the Global Navigation Satellite System (GNSS) L‐band microwave signal, measuring its attenuation by the canopy of a temperate broadleaf forest using a pair of GNSS receivers. This approach allowed us to collect continuous VOD observations at a sub‐hourly scale. We found a significant seasonal‐scale correlation between VOD and leaf water potential. The VOD diurnal amplitude is affected by soil moisture, plant transpiration and leaf surface water. Additionally, VOD can help independently estimate plant transpiration. Our findings pave the way for a deeper understanding of response of the vegetation to water stress at finer temporal scales.

Copyright and License (English)

© 2024. The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use andd istribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Acknowledgement (English)

This work was supported by NASA Carbon Cycle Science Grant 80NSSC21K1712. AGK was also supported by the Alfred P.Sloan Foundation.

Data Availability (English)

Ecosystem flux data for US-MOz is available at Wood and Gu (2022). Predawn leaf water potential measurement is available at Pallardy et al. (2018). CliMA-Land model is open-sourced, and is available at N. Holtzman (2023).

Supporting Information S1

Files

Geophysical Research Letters - 2024 - Yao - Investigating Diurnal and Seasonal Cycles of Vegetation Optical Depth Retrieved.pdf

Additional details

Created:
June 24, 2024
Modified:
June 24, 2024