Brown Bag Seminar: Tian Yao

USRA - NASA Goddard

 In previous studies, a widely-used way to estimate the vegetation gross primary production (GPP) is to use the fraction of photosynthetically radiation (PAR) absorbed by the entire vegetation canopy (fAPARcanopy) including both photosynthetic and non-photosynthetic canopy components. In this study, we have successfully developed an approach for canopies that determines the photosynthetic chlorophyll-containing canopy fraction (fAPARchl) separately from the non-photosynthetic component, which enables us to isolate and retrieve the fraction of absorbed PAR utilized for photosynthesis (i.e., fAPARPSN). The MODIS fAPARchl/LAIchl product is derived using a coupled canopy-leaf radiative transfer model (Zhang et al., 2005), which does not need any information of biome type as inputs. This product has been evaluated at selected flux tower sites with various plant functional types. The results show that MODIS fAPARchl/LAIchl product has the ability to better characterize phenology than the current model in the Community Land Model (CLM4.5), and to increase the accuracy of carbon flux simulations.

Tian Yao is currently a research scientist with Universities Space Research Association (USRA) working on improving the algorithm to produce MODIS fAPARchl/LAIchl product with parallel computing approaches, and implementation of the products into - ecosystem models (e.g. CLM 4.5). She received her PhD degree in Geography from Boston University, in 2012. Her PhD research was focused on measuring forest structure and biomass using ground-based and airborne lidar data. Her research interests include mapping, monitoring and modeling vegetation dynamics in response to climate change, and estimating terrestrial carbon flux, vegetation structure and biomass using ecosystem models and optical-lidar remote sensing data.