Global L-band equivalent AI-based vegetation optical depth dataset-Reference-Cited by-同舟云学术

Global L-band equivalent AI-based vegetation optical depth dataset

Published:2024-08-28 Issue:1 Volume:11 Page:
ISSN:2052-4463
Container-title:Scientific Data
language:en
Short-container-title:Sci Data

Author:

Skulovich Olya^ORCID,Li Xiaojun,Wigneron Jean-Pierre^ORCID,Gentine Pierre^ORCID

Funder

LEMONTREE (Land Ecosystem Models based on New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme

Centre National d'Etudes Spatiales

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41597-024-03810-2.pdf

Reference54 articles.

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2. Tian, F. et al. Coupling of ecosystem-scale plant water storage and leaf phenology observed by satellite. Nature ecology & evolution 2, 1428–1435, https://doi.org/10.1038/s41559-018-0630-3 (2018).

3. Konings, A. G., Holtzman, N. M., Rao, K., Xu, L. & Saatchi, S. S. Interannual variations of vegetation optical depth are due to both water stress and biomass changes. Geophysical Research Letters 48, e2021GL095267, https://doi.org/10.1029/2021GL095267 (2021).

4. Dou, Y. et al. Reliability of using vegetation optical depth for estimating decadal and interannual carbon dynamics. Remote Sensing of Environment 285, 113390, https://doi.org/10.1016/j.rse.2022.113390 (2023).

5. Wigneron, J.-P. et al. SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives. Remote Sensing of Environment 254, 112238, https://doi.org/10.1016/j.rse.2020.112238 (2021).