Wei Li

Research Associate Professor

School: School of Engineering and Science

Department: Physics

Building: Burchard

Room: 626

Phone: (201) 216-5580

Fax: (201) 216-5638

Email: wli4@stevens.edu

Education
  • MS (1985) Institute of Space Physics, Chinese Academy of Science (Space physics )
  • BS (1982) The University of Science and Technology of China (Space Physics)
Research

Application of machine learning technique in remote sensing.
Radiative transfer and related modeling: Coupled atmosphere-surface RT model including effects of polarization.
Remote sensing retrieval algorithm development aimed at combing visible, infrared, and microwave data for improved retrievals of surface and atmosphere properties.

General Information

1985 - 1997: Research Associate Professor, Institute of Atmospheric Physics, Chinese Academy of Sciences.
1997 – 2000: Research Associate, Geophysical Institute, University of Alaska Fairbanks.
2000 - present: Research Associate, Research Associate Professor, Stevens Institute of Technology.

Experience

Neural network technique applied to satellite remote sensing:
Snow/ice properties retrieval, Surface albedo retrieval;
Ocean color retrieval;
Long-term UV instrument data analysis
Multi-sensors data integration
Developed ocean color retrieval algorithms and water bio-optical models:
Atmospheric correction for heavy aerosol loadings;
Remote sensing reflectance retrieval for open ocean and coastal water;
Sun-glint reflectance simulation;
Algorithms for the GLI, SeaWiFS, MODIS, VIIRS, SGLI, and GOCI sensors.
Developed algorithm for NASA’s Cloud Absorption Radiometer (CAR) aircraft
instrument data to retrieve snow and ocean surface bi-directional reflectance values.
Radiative Transfer model improvement: the coupled atmosphere-snow/ice-ocean system and the effects of surface bi-directional reflectance.
Developed algorithms for JAXA’s GLobal Imager (GLI) on ADEOS-II:
Snow/ice properties retrieval;
Snow/ice surface temperature retrieval;
Cloud mask over snow.

Selected Publications
Conference Proceeding
  1. Gatebe, C.; Li, W.; Chen, N.; Fan, Y.; Poudyal, R.; Brucker, L.; Stamnes, K. (2018). Snow-covered area using machine learning techniques. International Geoscience and Remote Sensing Symposium (IGARSS) (vol. 2018-July, pp. 6291-6293).
    https://api.elsevier.com/content/abstract/scopus_id/85064194187.
Journal Article
  1. Sztipanov, M.; Tumeh, L.; Li, W.; Svendby, T.; Kylling, A.; Dahlback, A.; Stamnes, J. J.; Hansen, G.; Stamnes, K. (2020). Ground-based measurements of total ozone column amount with a multichannel moderate-bandwidth filter instrument at the Troll research station, Antarctica. Applied Optics (1 ed., vol. 59, pp. 97-106).
    https://api.elsevier.com/content/abstract/scopus_id/85077325496.
  2. Stamnes, K.; Hamre, B.; Stamnes, S.; Chen, N.; Fan, Y.; Li, W.; Lin, Z.; Stamnes, J. (2018). Progress in forward-inverse modeling based on radiative transfer tools for coupled atmosphere-snow/ice-ocean systems: A review and description of the AccuRT model. Applied Sciences (Switzerland) (12 ed., vol. 8).
    https://api.elsevier.com/content/abstract/scopus_id/85058677834.
  3. Chen, N.; Li, W.; Gatebe, C.; Tanikawa, T.; Hori, M.; Shimada, R.; Aoki, T.; Stamnes, K. (2018). New neural network cloud mask algorithm based on radiative transfer simulations. Remote Sensing of Environment (vol. 219, pp. 62-71).
    https://api.elsevier.com/content/abstract/scopus_id/85054464404.
  4. Tang, Q.; Hu, Y.; Li, W.; Huang, J.; Stamnes, K. (2018). Optimizing cirrus optical depth retrievals over the ocean from collocated CALIPSO and AMSR-E observations. Applied Optics (26 ed., vol. 57, pp. 7472-7481).
    https://api.elsevier.com/content/abstract/scopus_id/85052956408.