Articles | Volume 16, issue 1
https://doi.org/10.5194/essd-16-177-2024
https://doi.org/10.5194/essd-16-177-2024
Data description paper
 | 
10 Jan 2024
Data description paper |  | 10 Jan 2024

Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products

Xiangan Liang, Qiang Liu, Jie Wang, Shuang Chen, and Peng Gong

Related authors

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
Earth Syst. Sci. Data, 16, 5449–5475, https://doi.org/10.5194/essd-16-5449-2024,https://doi.org/10.5194/essd-16-5449-2024, 2024
Short summary

Cited articles

Barnes, W. L., Pagano, T. S., and Salomonson, V. V.: Prelaunch characteristics of the moderate resolution imaging spectroradiometer (MODIS) on EOS-AM1, IEEE T. Geosci. Remote, 36, 1088–1100, https://doi.org/10.1109/36.700993, 1998. 
Cao, R., Chen, Y., Shen, M., Chen, J., Zhou, J., Wang, C., and Yang, W.: A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter, Remote Sens. Environ., 217, 244–257, https://doi.org/10.1016/j.rse.2018.08.022, 2018. 
Cao, S., Li, M., Zhu, Z., Wang, Z., Zha, J., Zhao, W., Duanmu, Z., Chen, J., Zheng, Y., Chen, Y., Myneni, R. B., and Piao, S.: Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020, Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, 2023. 
Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturvedi, R. K., Fuchs, R., Brovkin, V., Ciais, P., Fensholt, R., Tømmervik, H., Bala, G., Zhu, Z., Nemani, R. R., and Myneni, R. B.: China and India lead in greening of the world through land-use management, Nat. Sustain., 2, 122–129, https://doi.org/10.1038/s41893-019-0220-7, 2019. 
Chen, J., Jönsson, P., Tamura, M., Gu, Z., Matsushita, B., and Eklundh, L.: A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter, Remote Sens. Environ., 91, 332–344, https://doi.org/10.1016/j.rse.2004.03.014, 2004. 
Download
Short summary
The state-of-the-art MODIS surface reflectance products suffer from temporal and spatial gaps, which make it difficult to characterize the continuous variation of the terrestrial surface. We proposed a framework for generating the first global 500 m daily seamless data cubes (SDC500), covering the period from 2000 to 2022. We believe that the SDC500 dataset can interest other researchers who study land cover mapping, quantitative remote sensing, and ecological science. 
Share
Altmetrics
Final-revised paper
Preprint