微波遥感

（1）全球水循环观测卫星计划  参与  中国科学院空间科学先导专项空间科学背景型号项目  2014.01—2015.12

（2）基于微波植被指数的L波段多角度数据反演土壤水分算法研究  负责人  国家自然科学基金青年项目  2014.01—2016.12

（3）遥感在泰国东北部水资源管理中的应用  负责人  国家重点研发计划政府间国际科技创新合作重点专项  2016.12—2018.12

（4）陆地水资源卫星系统多源数据融合与反演技术  负责人  国防科工局“十三五”民用航天预先研究项目  2017.01—2019.12

（5）基于L波段主被动微波遥感观测的地表冻融状态监测算法研究  负责人  国家自然科学基金面上项目  2017.01—2020.12

（6）积雪冻土时空变化的风云卫星遥感监测  负责人  中国气象局风云卫星应用先行计划项目  2022.07—2023.12

（7）陆地水循环关键参数时空多尺度智慧化遥感  参与  国家自然科学基金重大项目课题  2021.01—2025.12

（1）学术论文

[1]Hu, L., Zhao, T., Ju, W., Peng, Z., Shi, J., Rodríguez-Fernández, N. J., Wigneron, J.-P., Cosh, M. H., Yang, K., Lu, H., Yao, P. 2023. A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multi-channel collaborative algorithm. Remote Sensing of Environment, 292: 113595. (SCI)

[2]Wang, Z., Zhao, T., Shi, J., Wang, H., Ji, D., Yao, P., Zheng, J., Zhao, X., Xu, X. 2023. 1-km soil moisture retrieval using multi-temporal dual-channel SAR data from Sentinel-1 A/B satellites in a semi-arid watershed. Remote Sensing of Environment, 284: 113334. (SCI)

[3]Bai, Y., Zhao, T., Jia, L., Cosh, M. H., Shi, J., Peng, Z., Li, X., Wigneron, J.-P. 2022. A multi-temporal and multi-angular approach for systematically retrieving soil moisture and vegetation optical depth from SMOS data. Remote Sensing of Environment, 280: 113190. (SCI)

[4]Zheng, J., Zhao, T., Lü, H., Shi, J., Cosh, M. H., Ji, D., Jiang, L., Cui, Q., Lu, H., Yang, K., Wigneron, J.-P., Li, X., Zhu, Y., Hu, L., Peng, Z., Zeng, Y., Wang, X., Kang, C. S. 2022. Assessment of 24 soil moisture datasets using a new in situ network in the Shandian River Basin of China. Remote Sensing of Environment, 271: 112891. (SCI)

[5]Zhao, T., Shi, J., Entekhabi, D., Jackson, T. J., Hu, L., Peng, Z., Yao, P., Li, S., Kang, C. S. 2021. Retrievals of soil moisture and vegetation optical depth using a multi-channel collaborative algorithm. Remote Sensing of Environment, 257: 112321. (SCI)

[6]Zhao, T., Hu, L., Shi, J., Lü, H., Li, S., Fan, D., Wang, P., Geng, D., Kang, C. S., Zhang, Z. 2020. Soil moisture retrievals using L-band radiometry from variable angular ground-based and airborne observations. Remote Sensing of Environment, 248: 111958. (SCI)

[7]Zhao, T., Shi, J., Lv, L., Xu, H., Chen, D., Cui, Q., Jackson, T. J., Yan, G., Jia, L., Chen, L., Zhao, K., Zheng, X., Zhao, L., Zheng, C., Ji, D., Xiong, C., Wang, T., Li, R., Pan, J., … Zhang, Z. 2020. Soil moisture experiment in the Luan River supporting new satellite mission opportunities. Remote Sensing of Environment, 240: 111680. (SCI)

[8]Peng, B., Zhao, T., Shi, J., Lu, H., Mialon, A., Kerr, Y. H., Liang, X., Guan, K. 2017. Reappraisal of the roughness effect parameterization schemes for L-band radiometry over bare soil. Remote Sensing of Environment, 199: 63-77. (SCI)

[9]Zhao, T., Zhang, L., Jiang, L., Zhao, S., Chai, L., Jin, R. 2011. A new soil freeze/thaw discriminant algorithm using AMSR-E passive microwave imagery. Hydrological Processes, 25(11): 1704-1716. (SCI)

[10]Zhao, T. J., Zhang, L. X., Shi, J. C., Jiang, L. M. 2011. A physically based statistical methodology for surface soil moisture retrieval in the Tibet Plateau using microwave vegetation indices. Journal of Geophysical Research, 116: D08116. (SCI)

（2）专著（参与编写）

[1]《Observation and Measurement of Ecohydrological Processes》. Springer Berlin Heidelberg, 2020.

[2]《Comprehensive Remote Sensing：Vol 4 water cycle components over land》. Elsevier, 2018.

（1）2014年  国际无线电联盟（URSI）青年科学家奖

（2）2018年  国际电磁研究进展大会（PIERS）青年科学家奖

（3）2023年  李小文遥感科学青年奖