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Dr Jianglei XU

Postdoctoral Research Fellow

Education:

Ph.D. in Photogrammetry and Remote Sensing, Wuhan University (09/2020-06/2023)

M.S. in Cartography and Geographic Information Sciences, Beijing Normal University (09/2017-06/2020)

B.S. in Geographic Information Sciences (09/2013-06/2017)


Research Interests:

  • Earth energy budget, inversion algorithms development

  • high-level satellite products generation

  • spatiotemporal analysis on variations of earth energy budget


Publications:

  • Xu J., Liang S., Ma H., He T., Zhang Y., Zhang G. A daily 5-km all-sky sea-surface longwave radiation product based on statistically modified deep neural network and spatiotemporal analysis for 1981–2018. Remote Sensing of Environment 2023, 290: 113550.

  • Xu J., Liang S., He T., Ma H., Zhang Y., Zhang G., et al. Variability and trends in land surface longwave radiation fluxes from six satellite and reanalysis products. International Journal of Digital Earth 2023, 16(1): 2912-2940.

  • Xu, J., Liang, S., Ma, H., and He, T. Generating 5 km resolution 1981–2018 daily global land surface longwave radiation products from AVHRR shortwave and longwave observations using densely connected convolutional neural networks, Remote Sensing of Environment, 280, 113223, https://doi.org/10.1016/j.rse.2022.113223, 2022.

  • Xu, J., Liang, S., and Jiang, B. A global long-term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network, Earth Syst. Sci. Data, 14, 2315-2341, 10.5194/essd-14-2315-2022, 2022.

  • Xu, J., Jiang, B., Liang, S., Li, X., Wang, Y., Peng, J., Chen, H., Liang, H., and Li, S. Generating a High-Resolution Time-Series Ocean Surface Net Radiation Product by Downscaling J-OFURO3, IEEE Transactions on Geoscience and Remote Sensing, 2020.

  • Xu, J., Jiang, B. Downscaling Ocean Surface Net Radiation at Global Scales with Random Forest. IEEE International Geoscience and Remote Sensing Symposium (IGRASS), Yokohama, Japan, Anticipated in September 2019.

  • Jiang, B., Liang, S., Jia, A., Xu, J., Zhang, X., Xiao, Z., Zhao, X., Jia, K., and Yao, Y.: Validation of the surface daytime net radiation product from version 4.0 GLASS product suite, IEEE Geoscience and Remote Sensing Letters, 16, 509-513, 2018.

  • Zhang G., Liang S., Ma H., He T., Yin G., Xu J., et al. Simultaneous estimation of five temporally regular land variables at seven spatial resolutions from seven satellite data using a multi-scale and multi-depth convolutional neural network. Remote Sensing of Environment 2024, 301: 113928.

  • Liu X., Liang S., Ma H., Li B., Zhang Y., Li Y., He T., Zhang G., Xu J., Xiong C., et al. Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020. GIScience & Remote Sensing 2024, 61(1): 2300214.

  • Xiong C., Ma H., Liang S., He T., Zhang Y., Zhang G., Xu J. Improved global 250 m 8-day NDVI and EVI products from 2000–2021 using the LSTM model. Scientific Data 2023, 10(1): 800.

  • Zhang Y., Liang S., Ma H., He T., Wang Q., Li B., Xu J., Zhang G., et al. Generation of global 1-km daily soil moisture product from 2000 to 2020 using ensemble learning. Earth System Science Data Discussions 2023, 2023: 1-37.

Dr Jianglei XU
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