副教授

姓名：刘艳 

性别：女 

出生年月：1988年8月

职务/职称：副教授

邮箱：liuyan@gzhu.edu.cn

通讯地址：广州市大学城外环西路230号广州大学空天遥感创新研究院

刘艳，博士，副教授。2017年毕业于美国马萨诸塞大学波士顿分校，获哲学博士学位；2017年8月-2025年6月在中国科学院遥感与数字地球研究所、空天信息创新研究院工作；2025年7月起在广州大学空天遥感创新研究院工作。

主要从事遥感与GIS、国产卫星数据处理、BRDF反演与应用、物候遥感监测领域的教学与科研工作。主持国家自然科学基金青年基金1项，生态环境部委托项目1项，科技部国家重点研发计划任务/课题2项，国防科工局高分重大专项课题1项。曾开展NASA版本VIIRS载荷BRDF/反照率产品的研发、生产与验证工作，以第一作者身份撰写NASA版ATBD。共计发表 30 余篇学术论文。协助培养硕士生3人。

• 国产卫星数据处理

• BRDF反演与应用

• 物候遥感监测

• 2005.09－2009.06，兰州大学，获地理信息系统学士学位

• 2009.09－2012.06，北京师范大学，获定量遥感硕士学位

• 2012.09－2017.05，美国马萨诸塞大学波士顿分校，获环境科学博士学位

• 2017.07－2020.03，中国科学院遥感与数字地球研究所，助理研究员

• 2020.04－2025.06，中国科学院空天信息创新研究院，助理研究员

• 2020.01－2022.12，国家自然科学基金委员会青年科学基金项目（41901367），“基于中分辨率多星协同探索植被物候对京津冀城市化进程的响应”，经费30万元

• 2020.06－2023.05，科技部国家重点研发计划项目（2020YFE0200700），“面向‘一带一路’的定量遥感基础共性产品协同处理与联合验证关键技术联合研发”任务一（共性产品研发与生产），经费400万元

• 2020.11－2022.10，国防科工局高分重大专项（30-Y30F06-9003-20/22），“地球表层系统科学示范系统（二期）”（城市物候监测），经费120万元

• 2020.12－2023.11，科技部国家重点研发计划（2019YFE0127300），“中空间分辨率光谱地球研发与应用技术研究”任务一（多光谱处理技术），经费120万元

• 2024.11－2025.03，生态环境部卫星环境应用中心委托项目（AIRSY76-2024-000897），“GF501A卫星共性产品生产及算法研发”，经费29.9万元

【论文】

• Liang, M., Gu, X., Liu, Y.*, Cheng, T., Cao, H., Zhang, H., Zhang, Q., Ding, Y., Gao, M., Wei, X., & Zhan, Y. (2024). Preliminary Evaluation of Angular Reflectance Downscaling Using FSDAF Spatiotemporal Fusion Model and MODIS BRDF Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 5042–5058. https://doi.org/10.1109/JSTARS.2024.3365826

• Ding, Y., Gu, X., Liu, Y.*, Zhang, H., Cheng, T., Li, J., Wei, X., Gao, M., Liang, M., & Zhang, Q. (2023). GF-1 WFV Surface Reflectance Quality Evaluation in Countries along “the Belt and Road.” Remote Sensing, 15(22). https://doi.org/10.3390/rs15225382

• Zhang, Q., Gu, X., Liu, Y.*, Cheng, T., Liang, M., Ding, Y., Gao, M., Wei, X., & Li, J. (2023). A multi-feature combined cloud-snow differentiation algorithm for Gaofen-1 WFV data using temperature, temporal, and spectral characteristics. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1–14. https://doi.org/10.1109/JSTARS.2023.3325378

• Zhang, H., Zhang, X., Cui, L., Dong, Y., Liu, Y.*, Xi, Q., Cao, H., Chen, L., & Lian, Y. (2023). Enhancing Leaf Area Index Estimation with MODIS BRDF Data by Optimizing Directional Observations and Integrating PROSAIL and Ross–Li Models. Remote Sensing, 15(23). https://doi.org/10.3390/rs15235609

• Liu, Y., Gu, X., Cheng, T., Zhan, Y., Zhang, H., Li, J., Wei, X., Gao, M., Zhang, Q., & Zhang, Y. (2022). Temporal Shape–based Fusion Method to Generate Continuous Vegetation Index at Fine Spatial Resolution. IEEE Transactions on Geoscience and Remote Sensing, 60. https://doi.org/10.1109/TGRS.2022.3211269

• Gao, M., Liu, Y.*, Zhan, Y. L., Li, J., Gu, X., Maharjan, S. B., & Chen, X. (2022). A Modified NSPI Missing Information Reconstruction Method for MCD43A4 Over Nepal. International Geoscience and Remote Sensing Symposium (IGARSS), 2022-July, 1812–1815. https://doi.org/10.1109/IGARSS46834.2022.9884111

• Gao, M., Gu, X., Liu, Y.*, Zhan, Y., Wei, X., Yu, H., Liang, M., Weng, C., & Ding, Y. (2022). An Improved Spatiotemporal Data Fusion Method for Snow-Covered Mountain Areas Using Snow Index and Elevation Information. Sensors, 22(21), 8524. https://doi.org/10.3390/s22218524

• Liu, Y., McDonough MacKenzie, C., Primack, R. B., Hill, M. J., Zhang, X., Wang, Z., & Schaaf, C. B. (2021). Using remote sensing to monitor the spring phenology of Acadia National Park across elevational gradients. Ecosphere, 12(12). https://doi.org/10.1002/ecs2.3888

• Wang, D., Liu, Y., Yu, T., Zhang, Y., Liu, Q., Chen, X., & Zhan, Y. (2020). A method of using WRF-simulated surface temperature to estimate daily evapotranspiration. Journal of Applied Meteorology and Climatology, 59(5), 901–914. https://doi.org/10.1175/JAMC-D-19-0287.1

• Liu, Y., Hill, M. J., Zhang, X., Wang, Z., Richardson, A. D., Hufkens, K., Filippa, G., Baldocchi, D. D., Ma, S., Verfaillie, J., & Schaaf, C. B. (2017). Using data from Landsat, MODIS, VIIRS and PhenoCams to monitor the phenology of California oak/grass savanna and open grassland across spatial scales. Agricultural and Forest Meteorology, 237–238, 311–325. https://doi.org/10.1016/j.agrformet.2017.02.026(高被引论文)

• Liu, Y., Wang, Z., Sun, Q., Erb, A. M., Li, Z., Schaaf, C. B., Zhang, X., Román, M. O., Scott, R. L., & Zhang, Q. (2017). Evaluation of the VIIRS BRDF, Albedo and NBAR products suite and an assessment of continuity with the long term MODIS record. Remote Sensing of Environment, 201, 256–274.

• Liu, Y., Sun, Q., Wang, Z., Li, Z., Roman, M., Schaaf, C., VIIRS BRDF, Albedo, and NBAR Product Algorithm Theoretical Basis Document, NASA官方网站 https://viirsland.gsfc.nasa.gov/Products/NASA/AlbedoESDR.html

• Li, Z., Erb, A., Sun, Q., Liu, Y., Shuai, Y., Wang, Z., Boucher, P., & Schaaf, C. (2018). Preliminary assessment of 20-m surface albedo retrievals from sentinel-2A surface reflectance and MODIS/VIIRS surface anisotropy measures. Remote Sensing of Environment, 217(August), 352–365. https://doi.org/10.1016/j.rse.2018.08.025

• Zhang, X., Wang, J., Gao, F., Liu, Y., Schaaf, C., Friedl, M., Yu, Y., Jayavelu, S., Gray, J., Liu, L., Yan, D., & Henebry, G. M. (2017). Exploration of scaling effects on coarse resolution land surface phenology. Remote Sensing of Environment, 190, 318–330. https://doi.org/10.1016/j.rse.2017.01.001

• Wang, Z., Erb, A. M., Schaaf, C. B., Sun, Q., Liu, Y., Yang, Y., Shuai, Y., Casey, K. A., & Román, M. O. (2016). Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data. Remote Sensing of Environment, 185, 71–83. https://doi.org/10.1016/j.rse.2016.02.059

• Campagnolo, M. L., Sun, Q., Liu, Y., Schaaf, C., Wang, Z., & Román, M. O. (2016). Estimating the effective spatial resolution of the operational BRDF, albedo, and nadir reflectance products from MODIS and VIIRS. Remote Sensing of Environment, 175, 52–64. https://doi.org/10.1016/j.rse.2015.12.033

• 刘艳,王锦地,周红敏,薛华柱.2014.用地面点测量数据验证LAI产品中的尺度转换方法.遥感学报,18(6):1189-1198

• 刘艳, 王锦地, 周红敏, 薛华柱. 黑河中游试验区不同分辨率LAI数据处理、分析和尺度转换. 遥感技术与应用, 2010, 25(6): 805-813.

【专利/计算机软件著作权】

• 一种受云雪影响数据的重建方法, CN202210629380.X

• 一种数据重构方法及装置, CN202210356976.7

• 一种遥感物候监测结果验证方法，CP230908-2023113086688