Mariko Bürgin

Biography

Mariko Bürgin was born in Altdorf, Switzerland. She received the M.S. degree in Electrical Engineering and Information Technology from the Eidgenössische Technische Hochschule Zürich (ETH), Zurich, Switzerland, in 2008. She joined Mahta Moghaddam’s group in 2009 at University of Michigan, Ann Arbor, and received the M.S. degree in Electrical Engineering and Computer Science from the University of Michigan, Ann Arbor, USA, in 2011. Following the group’s transition in January 2012, she was a visiting scholar at the University of Southern California, Los Angeles, USA, while working remotely on her Ph.D. She received her doctoral degree in Electrical Engineering from the Radiation Laboratory of the Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, in December 2013. In 2014, she joined the Water and Carbon Cycles Group at the Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, USA, as a Caltech Postdoctoral Scholar.

Her research interests include forward and inverse modeling of electromagnetic scattering from vegetated areas with special interest in forests, radar systems, and radar measurements of vegetation and ground variables such as soil moisture. Her current research work is concerned with electromagnetic modeling for remote sensing applications, especially soil moisture remote sensing. Her current focus is on the improvement of the retrieval of soil moisture based on active microwave remote sensing over vegetated/forested areas by addressing important but often neglected aspects in radar imaging such as ionospheric effects, effects of multi species vegetation (heterogeneity at pixel level) and heterogeneity at landscape level. Her work is directly related to NASA’s Soil Moisture Active Passive (SMAP) and the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission.

 Mariko has regularly participated in many field campaigns, from ground truth collection (CanEx10 in Saskatchewan, Canada, SMAPEx3 in Yanco, Australia, SMAPVEX12 in Manitoba, Canada and many AirMOSS related field work in Arizona, Oregon, USA etc.) to wireless sensor node deployments as part of the Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) project.

Mariko is a member of IEEE, IEEE-GRSS and AGU.

Ph.D. Thesis
  • M. Burgin, Physics-based modeling for high-fidelity radar retrievals. University of Michigan, USA, Dec. 2013.
Master’s Thesis
  • M. Burgin, Ionospheric Effects on Low-Frequency Radar Signals. ETH Zurich, Switzerland, Aug. 2008.
Journal Papers (latest first)
  1. A. Tabatabaeenejad, M. Burgin, and M. Moghaddam, P-band radar retrieval of subcanopy and subsurface soil moisture profile as a second-order polynomial: First AirMOSS Results. IEEE Trans. Geosci. Remote Sensing, accepted for publication.
  2. U. Khankhoje, M. Burgin, and M. Moghaddam, On the accuracy of averaging radar backscattering coefficients for bare soils using the finite element method, IEEE Letters Geosci. Remote Sensing, in review.
  3. S. Kim, M. Moghaddam, L. Tsang, M. Burgin, X. Xu, and E. G. Njoku, Models of L-band radar backscattering coefficients over the global terrain for soil moisture retrieval. IEEE Trans. Geosci. Remote Sensing, in press.
  4. R. Magagi, A. Berg, K. Goita, S. Belair, T. Jackson, B. Toth, A. Walker, H. Mc-Nairn, P. O’Neill, M. Moghaddam, I. Gherboudj, A. Colliander, M. Cosh, J. Belanger, M. Burgin, J. Fisher, S. Kim, J. P. Rousseau, N. Djamai, J. Shang, and A. Merzouki, Canadian Experiment for soil moisture in 2010: Overview and preliminary results. IEEE Trans. Geosci. Remote Sensing, vol. 51, no. 1, pp. 347-363, Jan. 2013.
  5. A. Tabatabaeenejad, M. Burgin, and M. Moghaddam, Potential of L-band Radar for Retrieval of Canopy and Subcanopy Parameters of Boreal Forests. IEEE Trans. Geosci. Remote Sensing, vol. 50, no. 6, pp. 2150-2160, June 2012.
  6. M. Burgin, D. Clewley, R. M. Lucas, and M. Moghaddam, A generalized radar backscattering model based on wave theory for multilayer multispecies vegetation, IEEE Trans. Geosci. Remote Sensing, vol. 49, no. 12, pp. 4832–4845, Dec. 2011.
Conference Papers (latest first)
  1. M. Burgin and M. Moghaddam, Time-series analysis of L-band radar data over forested sites in SMAPVEX12. Presented at IEEE IGARSS 13, Melbourne, Australia, Jul. 2013.
  2. M. Burgin, A. Tabatabaeenejad, and M. Moghaddam, Scaling analysis of heterogeneity in support of soil moisture retrieval at landscape level for low-frequency radars. Presented at IEEE IGARSS 13, Melbourne, Australia, Jul. 2012.
  3. M. Burgin, A. Tabatabaeenejad, and M. Moghaddam, Analysis of impact of heterogeneity at landscape level in retrieval of soil moisture from low-frequency radar. Presented at AGU 12, San Francisco, USA, Dec. 2012.
  4. M. Burgin, A. Tabatabaeenejad, and M. Moghaddam, A generalized radar scattering model for multispecies forests with multilayer subsurface soil. In Proc. IEEE IGARSS, Munich, Germany, July 2012, pp. 5817-5819.
  5. A. Tabatabaeenejad, M. Burgin, and M. Moghaddam, Impact of subsurface layers on subcanopy soil moisture retrieval from radar. Presented at IEEE IGARSS 12, Munich, Germany, July 2012.
  6. M. Moghaddam, A. Tabatabaeenejad, M. Burgin, and X. Duan, Advances in radar forward and inverse scattering models of subsurface and subcanopy soil moisture and their role for the AirMOSS mission (invited). In Proc. IEEE IGARSS, Munich, Germany, July 2012, pp. 1274-1277.
  7. M. Burgin and M. Moghaddam, Investigating spatial aggregation techniques using a heterogeneous radar landscape simulator for reducing uncertainties of soil moisture retrieval from SMAP. In Proc. IEEE IGARSS, Vancouver, Canada, July 2011, pp. 265-268.
  8. A. Tabatabaeenejad, M. Burgin and M. Moghaddam, Retrieval of soil moisture and vegetation canopy parameters with L-band radar for a range of boreal forests. In Proc. IEEE IGARSS, Vancouver, Canada, July 2011, pp. 1211-1214.
  9. M. Burgin, A. Tabatabaeenejad, and M. Moghaddam, Utilizing CanEx-SM10 radar measurements for validation of vegetation model parameterization and canopy/subcanopy parameter retrieval. Presented at 32rd Canadian Symposium on Remote Sensing, Sherbrooke, Canada, Jun. 2011.
  10. M. Moghaddam, M. Burgin, A. Castillo, D. Entekhabi, Y. Goykhman, A. Kakhbod, K. Li, M. Liu, A. Nayyar, A. Silva, D. Teneketzis, Q. Wang, and X. Wu, Soil moisture sensing controller and optimal estimator (Soilscape): First deployment of the wireless sensor network and latest progress on soil moisture satellite retrieval validation strategies. In Proc. ESTF 2011, Pasadena, California, June 2011.
  11. M. Burgin and M. Moghaddam, A radar scattering landscape simulator for investigating multiscale spatial aggregation strategies. Presented at the National Radio Science Meeting, Boulder, Colorado, Jan. 2011.
  12. M. Moghaddam, M. Liu, X. Wu, K. Li, M. Burgin, Y. Goykhman, Q. Wang, D. Shuman, A. Nayyar, D. Teneketzis, and D. Entekhabi, Soil moisture sensing controller and optimal estimator (Soilscape): An in-situ wireless sensor network for validation of spaceborne soil moisture estimates (invited). Presented at American Geophysical Union Fall Conference, San Francisco, California, Dec. 2010.
  13. A. Tabatabaeenejad, M. Burgin, and M. Moghaddam, Sensitivity of SMAP radar retrieval of soil moisture to vegetation cover: analysis and field verification. In URSI-F Microwave Signatures Conference, Florence, Italy, Oct. 2010.
  14. M. Burgin, M. Moghaddam, and R. M. Lucas, Multilayered multiple species forest scattering model based on a wave theory approach (invited). Presented at IEEE IGARSS 10, Oahu, Hawaii, July 2010.
  15. M. Burgin, M. Moghaddam, and A. Freeman, Direct estimation of Faraday Rotation and other system distortion parameters from polarimetric SAR data. Presented at IEEE IGARSS 10, Oahu, Hawaii, July 2010.
  16. M. Burgin, D. Clewley, R. M. Lucas, and M. Moghaddam, Radar backscattering model for multispecies multilayer forests based on wave theory. Presented at the National Radio Science Meeting, Boulder, Colorado, Jan. 2010.
  17. M. Burgin, J. Jung, M. Moghaddam, and M. Crawford, Model-based integration of INSAR and Lidar for canopy structure. Presented at IEEE IGARSS 09, South Africa, July 2009.