Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5449-2024
https://doi.org/10.5194/essd-16-5449-2024
Data description paper
 | 
28 Nov 2024
Data description paper |  | 28 Nov 2024

Global 30 m seamless data cube (2000–2022) of land surface reflectance generated from Landsat 5, 7, 8, and 9 and MODIS Terra constellations

Shuang Chen, Jie Wang, Qiang Liu, Xiangan Liang, Rui Liu, Peng Qin, Jincheng Yuan, Junbo Wei, Shuai Yuan, Huabing Huang, and Peng Gong

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Cited articles

Abowarda, A. S., Bai, L., Zhang, C., Long, D., Li, X., Huang, Q., and Sun, Z.: Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale, Remote Sens. Environ., 255, 112301, https://doi.org/10.1016/j.rse.2021.112301, 2021. 
Battude, M., Al Bitar, A., Morin, D., Cros, J., Huc, M., Marais Sicre, C., Le Dantec, V., and Demarez, V.: Estimating maize biomass and yield over large areas using high spatial and temporal resolution Sentinel-2 like remote sensing data, Remote Sens. Environ., 184, 668–681, https://doi.org/10.1016/j.rse.2016.07.030, 2016. 
Bauer-Marschallinger, B. and Falkner, K.: Wasting petabytes: A survey of the Sentinel-2 UTM tiling grid and its spatial overhead, ISPRS J. Photogramm., 202, 682–690, https://doi.org/10.1016/j.isprsjprs.2023.07.015, 2023. 
Bolton, D. K., Gray, J. M., Melaas, E. K., Moon, M., Eklundh, L., and Friedl, M. A.: Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery, Remote Sens. Environ., 240, 111685, https://doi.org/10.1016/j.rse.2020.111685, 2020. 
Brooks, E. B., Thomas, V. A., Wynne, R. H., and Coulston, J. W.: Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis, IEEE T. Geosci. Remote, 50, 3340–3353, https://doi.org/10.1109/TGRS.2012.2183137, 2012. 
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Short summary
The inconsistent coverage of Landsat data due to its long revisit intervals and frequent cloud cover poses challenges to large-scale land monitoring. We developed a global 30 m 23-year (2000–2022) daily seamless data cube (SDC) of surface reflectance based on Landsat 5, 7, 8, and 9 and MODIS products. The SDC exhibits enhanced capabilities for monitoring land cover changes and robust consistency in both spatial and temporal dimensions, which are important for global environmental monitoring.
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