Qi, Wenlu

Bio

Wenlu received her Ph.D. degree in Geographical Sciences at the University of Maryland in 2018. She received the BS degree in Mechatronics Engineering from Beijing Institute of Technology in 2008 and the MS degree in Electrical Engineering from Chinese Academy of Sciences in 2011. Wenlu's interests mainly focus on the application of lidar and radar remote sensing on forest structure and biomass estimation. She has been a NASA Earth and Space Science fellow (NESSF) from 2014-2017 and is currently working on fusion between lidar data from NASA's Global Ecosystem Dynamics Investigation (GEDI) mission and Interferometric Synthetic Aperture Radar (InSAR) data from DLR's TerraSAR-X/TanDEM-X mission for improved forest biomass estimation over large areas.

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
  • Qi, W., Armston, J., Choi, C., Stovall, A., Saarela, S., Pardini, M., Fatoyinbo, L., Papathanasiou, K. & Dubayah R., 2023. Mapping Large-Scale Pantropical Forest Canopy Height by Integrating GEDI Lidar and TanDEM-X InSAR Data. Remote sensing of environment (second review)

  • 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, pp.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. and Gobakken, T., 2022. Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation. Remote Sensing of Environment, 278, p.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, July). Spaceborne Data Fusion for Large-Scale Forest Parameter Estimation: GEDI Lidar & Tandem-X INSAR Missions. In IGARSS 2019-2019 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, July). GEDI and TanDEM-X fusion for 3D forest structure parameter retrieval. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 380-382). IEEE.

  • Qi, W., & Dubayah, R. O. (2017, July). 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, June). 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.

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Personal Website(s)

Wenlu Qi Assistant Research Professor

Wenlu Qi
Assistant Research Professor

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

| wqi@umd.edu

| 3014053076