Research

Rui Cheng Lab - To see the unseeable

Our lab studies land surface processes and their feedbacks with climate using state-of-the-art remote sensing, process-based modeling, and machine learning, which motivates us to build advanced environmental sensors, develop land surface models, and make real-world impacts.

Gridded SIF

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We are maintaining a gridding code for satellite soundings. One available application is gridded TROPOMI SIF (instantaneous, day-length corrected, and relat...

CARBON: Remotely Estimating Carbon Uptake in the Arctic

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Opportunities and challenges in evaluating SIF-GPP relationship using SIF and machine learning-based GPP products Publications: Cheng, R. (2024), Solar-...

ENERGY: Radiative Transfer in Mountainous Regions

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Topographic dependence of radiation and vegetation dynamics. Publications: Kunik, L., Raczka, B., Smith, K.R., Bowling, D., Frankenberg, C., Köhler, P.,...

SENSING: Forest Ecology

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Multi-scale studies on the seasonality of SIF, hyperspectral reflectance, canopy color, and GPP from tropics to the Arctic. These papers feature a canopy-l...

WATER: Precipitation and Soil Moisture

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Long-term analyses on the climate dynamics and regional water fluxes. Publications: Cheng, R., Novak, L., & Schneider, T., 2021. Predicting the inte...