Qi, Wenlu

Bio

Wenlu received her Ph.D. degree in Geographical Sciences from the University of Maryland in 2018. She received a B.S. degree in Mechanical Electronics Engineering from Beijing Institute of Technology in 2008 and an M.S. degree in Electrical Engineering from the Chinese Academy of Sciences in 2011. Wenlu's research focuses on the application of lidar and radar remote sensing to forest structure, aboveground biomass, forest change, and uncertainty estimation. She was a NASA Earth and Space Science Fellow (NESSF) from 2014 to 2017. Since 2019, she has been collaborating with Ralph Dubayah, John Armston, Adrian Pascual, and other colleagues on the Dubayah NASA Carbon Monitoring System (CMS) project, developing GEDI-TanDEM-X data fusion approaches for pantropical forest structure, biomass, change, and uncertainty mapping. Her broader interests include lidar and synthetic aperture radar (SAR) data fusion for forest monitoring, with particular emphasis on GEDI, TanDEM-X, NISAR, BIOMASS, and future missions such as EDGE.

Degrees

  • Geographical Sciences, University of Maryland - Ph.D

  • Electrical Engineering, Chinese Academy of Sciences - MS

  • Mechatronics Engineering, Beijing Institute of Technology - BS

Areas of Interest

  • Forest structure and biomass mapping
  • Lidar and radar remote sensing

Research Topics

  • Carbon, Vegetation Dynamics and Landscape-Scale Processes
  • Geospatial Information Science and Remote Sensing

Xie, Y., Dubayah, R., Qi, W., & Armston, J. (2026). Improved large-scale pantropical forest canopy height mapping by integrating GEDI lidar, TanDEM-X, and BIOMASS InSAR data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2026).

Qi, W., Armston, J., Xie, Y., Pascual, A., de Conto, T., Basargin, N., Papathanassiou, K., Pardini, M., & Dubayah, R. (in preparation for 2026 submission). From canopy structure to carbon change: Forest structure and biomass dynamics in the Congo Basin, 2010-2025 from GEDI-TanDEM-X data fusion. Environmental Research Letters.

Qi, W., Armston, J. D., Dubayah, R., Pascual, A., de Conto, T., Basargin, N., Papathanassiou, K., & Pardini, M. (2025). Advancing high-resolution forest structure, biomass, and change estimation in ASEAN countries through GEDI-TanDEM-X fusion. AGU Fall Meeting 2025, Session B23H: Carbon Monitoring Systems Research and Applications II, New Orleans, LA, 16 December 2025.

Qi, W., Armston, J., Dubayah, R., Pascual, A., Saarela, S., Basargin, N., Papathanassiou, K., & Pardini, M. (2025). Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. Remote Sensing of Environment, 318, 114534. https://doi.org/10.1016/j.rse.2024.114534

Qi, W., Armston, J., Choi, C., Stovall, A., Saarela, S., Pardini, M., Fatoyinbo, L., Papathanassiou, K., Pascual, A., & Dubayah, R. (2024). Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. AGU Fall Meeting.

Dubayah, R. O., Qi, W., Armston, J., Fatoyinbo, L., Papathanassiou, K., Pardini, M., Stovall, A., Choi, C., & Cazcarra-Bes, V. (2023). Pantropical forest height and biomass from GEDI and TanDEM-X data fusion (Version 1). ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/2298

Choi, C., Cazcarra-Bes, V., Guliaev, R., Pardini, M., Papathanassiou, K. P., Qi, W., Armston, J., & Dubayah, R. O. (2023). Large-scale forest height mapping by combining TanDEM-X and GEDI data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 2374-2385.

Saarela, S., Holm, S., Healey, S. P., Patterson, P. L., Yang, Z., Andersen, H. E., Dubayah, R. O., Qi, W., Duncanson, L. I., Armston, J. D., & Gobakken, T. (2022). Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation. Remote Sensing of Environment, 278, 113074.

Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., Armston, J., Tang, H., Duncanson, L., Hancock, S., Jantz, P., Marselis, S., Patterson, P., Qi, W., & Silva, C. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography. Science of Remote Sensing, 1, 100002.

Qi, W., Saarela, S., Armston, J., Ståhl, G., & Dubayah, R. (2019). Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data. Remote Sensing of Environment, 232, 111283.

Qi, W., Lee, S. K., Hancock, S., Luthcke, S., Tang, H., Armston, J., & Dubayah, R. (2019). Improved forest height estimation by fusion of simulated GEDI lidar data and TanDEM-X InSAR data. Remote Sensing of Environment, 221, 621-634.

Pardini, M., Armston, J., Qi, W., Lee, S. K., Tello, M., Bes, V. C., & Fatoyinbo, L. E. (2019). Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization. Surveys in Geophysics, 40(4), 803-837.

Lee, S. K., Fatoyinbo, T., Marselis, S. M., Qi, W., Hancock, S., Armston, J., & Dubayah, R. (2019). Spaceborne data fusion for large-scale forest parameter estimation: GEDI lidar and TanDEM-X InSAR missions. In IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 4491-4494). IEEE.

Qi, W. (2018). Fusing GEDI lidar and TanDEM-X InSAR observations for improved forest structure and biomass mapping. Doctoral dissertation.

Lee, S. K., Fatoyinbo, T., Qi, W., Hancock, S., Armston, J., & Dubayah, R. (2018). GEDI and TanDEM-X fusion for 3D forest structure parameter retrieval. In IGARSS 2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 380-382). IEEE.

Qi, W., & Dubayah, R. O. (2017). Forest structure modeling of a coniferous forest using TanDEM-X InSAR and simulated GEDI lidar data. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 914-917). IEEE.

Qi, W., & Dubayah, R. O. (2016). Combining TanDEM-X InSAR and simulated GEDI lidar observations for forest structure mapping. Remote Sensing of Environment, 187, 253-266.

Pardini, M., Qi, W., Dubayah, R., & Papathanassiou, K. P. (2016). Exploiting TanDEM-X Pol-InSAR data for forest structure observation and potential synergies with NASA’s Global Ecosystem Dynamics Investigation lidar. In Proceedings of EUSAR 2016: 11th European Conference on Synthetic Aperture Radar (pp. 1-6). VDE.

 

Personal Website(s)

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Wenlu Qi
Assistant Research Professor

| 4600 River Road, Suite 347E3 (send mail to 2181 LeFrak)

| wqi@umd.edu

| 3014053076

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