Rui Cheng

Rui Cheng in a professional headshot smiles with her long black hair pulled in front of her right shoulder, wearing a gold turtleneck knitted sweater
Assistant Professor
[email protected]
220-B BioAgEng Building

1390 Eckles Ave.
St. Paul, MN 55108
United States

Cheng Lab: Environmental Sensing and Modeling
Education
Ph.D. Caltech 2022; M.S. Caltech 2019
M.S. Lehigh University 2017 
B.S. Sun Yat-sen University 2015

Areas of Interest

Remote Sensing, Solar-Induced Chlorophyll Fluorescence, Hyperspectral Imaging, Land-Climate Feedbacks, Surface Process Modeling

Research

The research goal of Cheng Lab is to better project the potential of terrestrial ecosystems as a natural-based solution for mitigating climate change. Current research projects provide new insights into the productivity of terrestrial ecosystems and the complicated feedbacks between plants and climate using advanced remote sensing techniques. Cheng Lab explores the full potential of emitted and reflected radiation from the Earth's surface, e.g., Solar-Induced Chlorophyll Fluorescence (leaf glows!), to infer the carbon, water, and energy transport through the continuum of soil-plant-atmosphere. With these new insights, Cheng Lab works towards better estimating the amount of carbon plants can remove from the atmosphere under the changing climate, especially in understudied and challenging areas without easy access, such as the Arctic, the tropics, and mountains.

Select Publications

Cheng, R., Magney, T.S., Orcutt, E.L., Pierrat, Z., Köhler, P., Bowling, D.R., Bret-Harte, M.S., Euskirchen, E.S., Jung, M., Kobayashi, H., Rocha, A.V., Sonnentag, O., Stutz, J., Walther, S., Zona, D., Frankenberg, C. Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence (2022). Environmental Research Letters. https://doi.org/10.1088/1748-9326/ac9dae 

Cheng, R., Köhler, P., and Frankenberg, C. Impacts of topography and radiation on temporal upscaling of instantaneous solar-induced chlorophyll fluorescence (2022). Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2022.109197 

Cheng, R., Novak, L., and Schneider, T., Predicting the interannual variability of California’s total annual precipitation (2020). Geophysical Research Letters, 48, e2020GL091465. https://doi.org/10.1029/2020GL091465 

Cheng, R., Magney, T.S., Dutta, D., Bowling, D.R., Logan, B.A., Burns, S.P., Blanken, P.D., Grossmann, K., Lopez, S., Richardson, A.D. and Stutz, J. Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest (2020). Biogeosciences, 17(18), pp.4523-4544. https://doi.org/10.5194/bg-17-4523-2020 

Magney, T.S., Bowling, D.R., Logan, B.A., Grossmann, K., Stutz, J., Blanken, P.D., Burns, S.P., Cheng, R., Garcia, M.A., Kӧhler, P. and Lopez, S., Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence (2019). Proceedings of the National Academy of Sciences, 116(24), pp.11640-11645. https://doi.org/10.1073/pnas.1900278116 

Byrne, B., Liu, J., Yi, Y., Chatterjee, A., Basu, S., Cheng, R., Doughty, R., Chevallier, F., Bowman, K.W., Parazoo, N. C., Crisp, D., Li, X., Xiao, J., Sitch, S., Guenet, B., Deng, F., Johnson, M. S., Philip, S., Mcguire, P. C., and Miller, C. E. Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia (2022). Biogeosciences. https://doi.org/10.5194/bg-19-4779-2022 

Seyednasrollah, B., Bowling, D.R., Cheng, R., Logan, B.A., Magney, T.S., Frankenberg, C., Yang, J.C., Young, A.M., Hufkens, K., Arain, M.A. and Black, T.A. Seasonal variation in the canopy color of temperate evergreen conifer forests (2020). New Phytologist. https://doi.org/10.1111/nph.17046 

Felzer, B.S., Ember, C.R., Cheng, R. and Jiang, M. The Relationships of Extreme Precipitation and Temperature Events with Ethnographic Reports of Droughts and Floods in Nonindustrial Societies (2020). Weather, Climate, and Society, 12(1), pp.135-148. https://doi.org/10.1175/WCAS-D-19-0045.1 

Zhang, D., Qiu, G., Gao, Y., Fang, X., Cheng, R., Chang, A. and Chan, C.Y. Crowdsourcing based radio map anomalous event detection system for calibration-on-demand (2014). In 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 220-229). IEEE.

PhD and Postdoc opportunities are available. Please reach out if you are interested in sensing and modeling in terrestrial ecosystems.