EMDO Scientists Presented at AGU Annual Conferences in Dec 2018

EMDO senior research scientists, Dr. Liming He and Dr. Jianjun Liu, attended the American Geophysical Union’s (AGU) Fall Meeting (AGU) held during early December 2018 in Washington, D.C. Dr. He presented an oral presentation entitled “High and diverse photosynthetic capacity of global farmland illustrated by satellite chlorophyll fluorescence measurements” which was highlighted by the session conveners. In the atmospheric session, Dr. Liu gave an oral presentation entitled “Estimating Hourly PM2.5 Concentration from Satellite Measured Top of Atmosphere Reflectance by Using a Machine Learning Algorithm”

In Dr. He’s presentation, he introduced the method to derive Rubisco-limited photosynthetic capacity (i.e. maximum carboxylation rate, Vcmax), a plant functional trait that strongly influences to global carbon and water cycles, from 11-year-long satellite chlorophyll fluorescence measurements. The derived Vcmax product reveals the large seasonal and spatial variations of Vcmax for different crop rotation systems and the emerging soybean revolution in South America. This study suggests that satellite chlorophyll fluorescence is not only powerful in monitoring the terrestrial ecosystem productivity but also useful for deriving the important plant functional trait Vcmax for process-based modeling of terrestrial ecosystems.

Dr. Liu’s presentation introduced a novel method to estimate the surface PM2.5 concentrations based on an ensemble machine learning algorithm by directly using the satellite measured top-of-atmosphere (TOA) reflectance as inputs instead of aerosol optical depth (AOD), which is used in most previous studies. The algorithm is demonstrated to perform well across China with high accuracies at different temporal scales. The accuracies of the estimation on PM2.5 concentration by using TOA reflectance directly are comparable with those of the common methods on estimating PM2.5 concentration by using satellite-derived AOD, but the former has a relatively stronger predictive power relating to spatial-temporal coverages than the latter. This study proposes a short-cut solution for PM2.5 concentration estimations from satellite observations by directly using TOA reflectance which can circumvent the numerous sources of errors in the retrievals of AOD.

Dr. He led the above-mentioned collaborative study when he was at the University of Toronto. After he joined EMDO, he continues to refine this study for agricultural applications. Dr. Liu has engaged in a wide range of studies concerning remote sensing of air pollution and their impact on the radiation, cloud and climate issues. ¯Ú The AGU 2018 fall meeting marked another dynamic year of discovery in earth and space science. Exploration of many dimensions of science’s impact on society inspired our young scientists to grow more innovations, predictable solutions to the undiscovered world and gain visions on connecting worldwide scientific experiences.






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