Biography
I am a postdoctoral research associate at the Geospatial Sciences Center of Excellence, South Dakota State University. I joined SDSU in 2022. Prior to this, I received my Ph.D. in environmental science from the University of Technology Sydney, Australia (2017-2022) and my M.S. in electronic and communication engineering from the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, China (2014-2017). Since joining SDSU, my research has primarily focused on investigating species-specific vegetation phenological dynamics using fine-resolution commercial satellite data and developing enhanced land surface phenology products by integrating multiscale remote sensing observations in dryland ecosystems.
My research interests center on the application of remote sensing to environmental monitoring and ecological analysis. I am particularly interested in satellite-based detection of vegetation phenology, landscape dynamics and the integration of multisource Earth observation data to support the understanding of land surface processes and environmental change.
My research interests center on the application of remote sensing to environmental monitoring and ecological analysis. I am particularly interested in satellite-based detection of vegetation phenology, landscape dynamics and the integration of multisource Earth observation data to support the understanding of land surface processes and environmental change.
Research and Scholarly Work
Awards and Honors
Maxar Spatial Challenge 2020, second prize
Maxar Technologies, Arlula Pty Led., Consilium Technology, Australia
Publications
- Liu, Y., Zhang, X., Tran, K.H., Ye, Y., Shen, Y., An, S., 2025, Heterogeneous land surface phenology challenges the comparison among PlanetScope, HLS and VIIRS detections in semiarid rangelands, Agricultural and Forest Meteorology, 366, 110497, DOI: 10.1016/j.agrformet.2025.110497
- Tran, K.H., Zhang, X., Zhang, H.K., Shen, Y., Ye, Y., Liu, Y., Gao, S., An, S., 2025, A transformer-based model for detecting land surface phenology from the irregular harmonized Landsat and Sentinel-2 time series across the United States, Remote Sensing of Environment, 320, 114656, DOI: 10.1016/j.rse.2025.114656
- Shen, Y., Zhang, X., Tran, K.H., Ye, Y., Gao, S., Liu, Y., An S., 2025, Near real-time corn and soybean mapping at field-scale by blending crop phenometrics with growth magnitude from multiple temporal and spatial satellite observations, Remote Sensing of Environment, 318, 114605, DOI: 10.1016/j.rse.2025.114605
- Zhu, X., Ma, X., Zhang, Z., Liu, Y., Luo, Y., Yan, K., Pei, T., Huete, A., 2024, Floating in the air: forecasting allergenic pollen concentration for managing urban public health, International Journal of Digital Earth, 17 (1), 2306894, DOI: 10.1080/17538947.2024.2306894
- Ma, X., Huete, A., Liu, Y., Zhu, X., Nguyen, H., Miura, T., Chen, M., Li, X., Asrar, G., 2024, A holistic big data approach to understand and manage increasing pollen‐induced respiratory allergies under global change, Global Change Biology, 30 (8), e17451, DOI: 10.1111/gcb.17451
- Liu, Y., Zhang, X., Shen, Y., Ye, Y., Gao, S., Tran, K.H., 2024, Evaluation of PlanetScope-detected plant-specific phenology using infrared-enabled PhenoCam observations in semi-arid ecosystems, ISPRS Journal of Photogrammetry and Remote Sensing, 210, 242-259, DOI: 10.1016/j.isprsjprs.2024.03.017
- Shen, Y., Zhang, X., Gao, S., Zhang, H.K., Schaaf, C., Wang, W., Ye, Y., Liu, Y., Tran, K.H., 2024, Analyzing GOES-R ABI BRDF-adjusted EVI2 time series by comparing with VIIRS observations over the CONUS, Remote Sensing of Environment, 302, 113972, DOI: 10.1016/j.rse.2023.113972
- Shen, Y., Zhang, X., Yang, Z., Ye, Y., Wang, J., Gao, S., Liu, Y., Wang, W., Tran, H.K., Ju, J., 2023, Developing an operational algorithm for near-real-time monitoring of crop progress at field scales by fusing harmonized Landsat and Sentinel-2 time series with geostationary satellite observations. Remote Sensing of Environment, 296: 113729, DOI: 10.1016/j.rse.2023.113729
- Tran, H.K., Zhang, X., Ye, Y., Shen, Y., Gao, S., Liu, Y., Richardson, A.D., 2023, HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data. Scientific Data, 10: 691, DOI: 10.1038/s41597-023-02605-1
- Ma, X., Zhu, X., Xie, Q., Jin, J., Zhou, Y., Luo, Y., Liu, Y., Tian, J., Zhao, Y., 2022, Monitoring nature’s calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications. Global Change Biology, 28:7186-7204, DOI: 10.1111/gcb.16436
- Abdollahi, A., Liu, Y., Pradhan, B., Huete, A., Dikshit, A., Tran N.N., 2022, Short-time-series grassland mapping using Sentinel-2 imagery and deep learning-based architecture. The Egyptian Journal of Remote Sensing and Space Science, 25: 673-685, DOI: 10.1016/j.ejrs.2022.06.002
- Thomas, L., Wilkinson, S. J., Wyndham, J., Huete, A., Biloria, N., Woods, A., Kalali, P., Powles R., Srivastave A., Liu, Y., Bulut, M., Dritsa, D., Runck, M., Dwyer, S., 2022, Fairwater Living Laboratory Milestone 4 UTS Research Report Outcomes for Energy, Network Demand, Residents and Community, Resilience, Urban Heat Effects and Commerciality. University of Technology Sydney, Technical report.
- Liu, Y., Wu, C., Peng, D., Xu, S., Gonsamo, A., Jassal, R. S., Arain, M. A., Lu, L., Fang, B., Chen, J. M., 2016, Improved modelling of land surface phenology using MODIS land surface reflectance and temperature at evergreen needleleaf forests of central North America. Remote Sensing of Environment, 176:152-162, DOI: 10.1016/j.rse.2016.01.021
