Xu, Shuo | GEOG | Geographical Sciences Department

Shuo Xu is a doctoral student and Research Graduate Assistant at the University of Maryland in the Department of Geographical Sciences. She earned a B.Eng degree in Remote Sensing Science and Technology from Shandong University of Science and Technology (Qingdao), China, and an M.S. in Cartography and Geographical information system from Beijing Normal University, China. Her areas of interest include climate change, land surface temperature, data retrieval, data downscaling, data fusion and machine learning.

CV:

Degrees

Degree Type

MS

Degree Details

Beijing Normal University

Awards

2022-10-19

Jacob K. Goldhaber Travel Grant
2024-05-10

Excellence in Graduate Research Award (third place)
2024-05-10

Jingli Yang Summer Research Fellowship
2024-05-10

Outstanding Graduate Research Assistant Award

Conferences

2022

AGU 2022
2023

2023 CoRP Science Symposium

Research Topics

Geospatial-Information Science and Remote Sensing

Jia, A., et al.: Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data, Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, 2023.
Jia, A., Liang, S., Wang, D., Mallick, K., Zhou, S., Hu, T., & Xu, S. (2024). Advances in Methodology and Generation of All-Weather Land Surface Temperature Products From Polar-Orbiting and Geostationary Satellites: A comprehensive review. IEEE Geoscience
Xu, S., Wang, D., Liang, S., Jia, A., Li, R., Wang, Z., & Liu, Y. (2024). A novel approach to estimate land surface temperature from landsat top-of-atmosphere reflective and emissive data using transfer-learning neural network. Science of The Total
Xu, S., Wang, D., Liang, S., Liu, Y., & Jia, A. (2023). Assessing the reliability of the MODIS LST product to detect temporal variability. IEEE Geoscience and Remote Sensing Letters.
Xu, S., Wang, D., Liang, S., Liu, Y., & Jia, A. (2023). Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias.
Xu, Shuo, and Jie Cheng. "A new land surface temperature fusion strategy based on cumulative distribution function matching and multiresolution Kalman filtering." Remote Sensing of Environment 254 (2021): 112256.
Xu, Shuo, Jie Cheng, and Quan Zhang. "A Random Forest-Based Data Fusion Method for Obtaining All-Weather Land Surface Temperature with High Spatial Resolution." Remote Sensing 13.11 (2021): 2211.
Xu, Shuo, Jie Cheng, and Quan Zhang. "Reconstructing all-weather land surface temperature using the bayesian maximum entropy method over the Tibetan plateau and Heihe river basin."
Zhang Q, ..., Xu S. A stepwise downscaling method for generating high-resolution land surface temperature from AMSR-E data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 5669-5681.

4600 River Road

Department of Geographical Sciences

shuoxu98 [at] umd.edu