Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-2849-2025
https://doi.org/10.5194/essd-17-2849-2025
Data description paper
 | 
24 Jun 2025
Data description paper |  | 24 Jun 2025

A global daily seamless 9 km vegetation optical depth (VOD) product from 2010 to 2021

Die Hu, Yuan Wang, Han Jing, Linwei Yue, Qiang Zhang, Lei Fan, Qiangqiang Yuan, Huanfeng Shen, and Liangpei Zhang

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2024-411', Anonymous Referee #1, 14 Feb 2025
    • AC1: 'Reply on RC1', Qianqqiang Yuan, 15 Mar 2025
  • RC2: 'Comment on essd-2024-411', Anonymous Referee #2, 25 Feb 2025
    • AC2: 'Reply on RC2', Qianqqiang Yuan, 15 Mar 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Qianqqiang Yuan on behalf of the Authors (15 Mar 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (29 Mar 2025) by Yuqiang Zhang
AR by Qianqqiang Yuan on behalf of the Authors (31 Mar 2025)  Manuscript 
Download
Short summary
Existing L-band vegetation optical depth (L-VOD) products suffer from data gaps and coarse resolution of historical data. Therefore, it is necessary to integrate multi-temporal and multisource L-VOD products. Our study begins with the reconstruction of missing data and then develops a spatiotemporal fusion model to generate global daily seamless 9 km L-VOD products from 2010 to 2021, which are crucial for understanding the global carbon cycle.  
Share
Altmetrics
Final-revised paper
Preprint