Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1016/j.jag.2025.104961 |
Lizenz  |
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| Titel (primär) | A global long-term (2002–2022) C-band vegetation optical depth record retrieved after merging AMSR-E, AMSR2 and WindSat |
| Autor | Chen, D.; Fan, L.; Peng, J.
; De Lannoy, G.; Wigneron, J.-P.; Frappart, F.; Tao, S.; Wang, M.; Li, X.; Liu, X.; Wang, H.; Yuan, Q.; Chen, X.; Xiao, Y.; Ciais, P. |
| Quelle | International Journal of Applied Earth Observation and Geoinformation |
| Erscheinungsjahr | 2025 |
| Department | RS |
| Band/Volume | 145 |
| Seite von | art. 104961 |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Daten-/Softwarelinks | https://doi.org/10.5281/zenodo.17359730 |
| Supplements | Supplement 1 |
| Keywords | Vegetation; Optical Depth; Microwave Remote Sensing; AMSR-E/AMSR2/WindSat; Sensor merging |
| Abstract | Vegetation optical depth (VOD) based on microwave remote sensing has become an essential indicator for monitoring large-scale vegetation conditions. The relatively long-term record of satellite-based passive C-band observations offers the potential for assessing dynamic vegetation changes. Due to the limited operational lifetime of individual microwave sensors, retrieving a long-term C-band VOD (C-VOD) dataset often requires combining multiple sensors, such as Advanced Microwave Scanning Radiometer for EOS Aqua (AMSR-E, 2002–2011), Advanced Microwave Scanning Radiometer 2 (AMSR2, 2012–present) and WindSat (2003–2020). Retrieving a long-term C-VOD from their C-band brightness temperature (TB) observations faces two major challenges: (i) non-negligible systematic biases exist between the TB observations among the three sensors; (ii) TB from different sensors may not be strongly associated, especially in tropical forests with small seasonal variations. To address these challenges, we employed a combined inter-calibration method, using linear regression in sparse vegetation and linear rescaling in dense vegetation, to merge TB from three sensors. Results showed that: (i) in undisturbed dense forests where minimal emissivity variation can be assumed, the merged TB (2002–2022) exhibited strong temporal correlations with skin temperature (H polarization: R = 0.90, V polarization: R = 0.86); (ii) the merged C-VOD retrieved from the merged TB exhibited substantially improved temporal consistency across three sensors, reducing global discrepancies between AMSR-E and AMSR2 from 6.20 % to 0.34 %. Furthermore, the merged C-VOD showed stable long-term consistency across sensors, with paired t-tests indicating no significant differences (P-value > 0.01) at the global and vegetation-type scales, confirming reliable cross-sensor continuity; (iii) the merged C-VOD showed stronger temporal correlations with normalized difference vegetation index, enhanced vegetation index, and site-level gross primary production across more vegetated areas globally, and exhibited higher and more stable spatial correlations with vegetation variables across sensor transitions compared to the existing merged C-VOD product. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31900 |
| Chen, D., Fan, L., Peng, J., De Lannoy, G., Wigneron, J.-P., Frappart, F., Tao, S., Wang, M., Li, X., Liu, X., Wang, H., Yuan, Q., Chen, X., Xiao, Y., Ciais, P. (2025): A global long-term (2002–2022) C-band vegetation optical depth record retrieved after merging AMSR-E, AMSR2 and WindSat Int. J. Appl. Earth Obs. Geoinf. 145 , art. 104961 10.1016/j.jag.2025.104961 |
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