Spatiotemporal coverage capability of moon-based SAR for water dynamic monitoring in global vegetation tipping elements

ABSTRACT

Changes in water content dynamics can serve as predictive indicators for catastrophic transitions in vegetation tipping elements. Vegetation water content is a rapidly changing parameter with sub-daily fluctuations, and current space-borne sensors fall short of providing adequate spatiotemporal coverage for effective analysis. The Moon-based Earth observation, i.e. Synthetic Aperture Radar has recently showcased prolonged durations, rapid revisiting rates, and extensive monitoring capabilities with a decent spatial resolution (10-100 m). This opens up new possibilities for vegetation water content monitoring which has not yet been discussed. The study has assessed its monitoring capability in four critical vegetation tipping elements and considered both overall temporal observation availability fraction and diurnal variation acquisition. The results indicate that Amazon and Sahelian regions can be observed for ∼30% of a nutation period (∼18.6 years). Diurnal variations in water content can be captured with a 1-hour interval every 16–23 days for the Amazon and Sahelian regions. For polar tundra and boreal regions, continuous observation spanning 7–12 h can be achieved. These outstanding characteristics offer a deeper understanding of water content dynamics in vegetation tipping elements, which will enhance our prediction for their critical transitions.

KEYWORDS:

• Moon-based earth observation
• vegetation water content
• tipping elements
• synthetic aperture radar

Acknowledgements

The authors express their gratitude to the IAU SOFA Collection for generously permitting its use, with copyright © International Astronomical Union Standards of Fundamental Astronomy (http://www.iausofa.org). The authors would also like to thank JPL for providing free access to DE430 and to the IERS for sharing EOP data. Additionally, the authors appreciate Google Developers for granting us free access to the RESOLVE Ecoregions dataset (https://developers.google.com/earth-engine/datasets) and Olson’s work in World Terrestrial Ecoregions. Information on the FLUXNET data was shared by the FLUXNET community, including these networks: AmeriFlux and AfriFlux.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Key Research and Development Program of China (2022YFB3902100) and the National Science Foundation of China (42276241) and in part by the National Science Foundation of China (42301403).