PS 72-116
EO-1 Hyperion reflectance time series tracing the seasonal dynamics in vegetation bio-physical parameters

Thursday, August 13, 2015
Exhibit Hall, Baltimore Convention Center
Petya Campbell, UMBC and NASA/GSFC, Greenbelt, MD
Elizabeth Middleton, NASA, g, MD
Karl Huemmrich, NASA, Greenbelt, MD

Satellite hyeprspectral remote sensing is essential for monitoring vegetation physiology, phenology and spatial variation, to assess the impact of terrestrial ecosystems on the dynamics of carbon fluxes and improve our understanding of the underlying factors. High spectral resolution measurements (≤10 nm, 400-2500 nm) provide an efficient tool for synoptic evaluation of many of the factors significantly affecting the ability of the vegetation to sequester carbon and to reflect radiation, due to changes in vegetation chemical and structural composition.

This study presents the results of the analysis of Earth Observing-1 (EO-1) Hyperion data in comparison to CO2 flux estimates at a number of LTER and FLUXNET sites. EO-1 Hyperion seasonal composites were assembled and the radiance data were corrected for atmospheric effects. Spectral bio-indicators were computed from surface reflectance spectra collected in the flux tower footprints and compared to field flux tower measurements (e.g., CO2 flux, μmol m-2 s-1).


We evaluated the dynamics in canopy leaf area, chlorophyll content, moisture and photosynthesis for the following major vegetation types: northern hardwood forest, grassland, evergreen coniferous forest, savanna, woodland, rain forest and mangrove forest. Spectral differences and seasonal trends were established for each vegetation type and site specific phenology. Comparing spectral parameters in these vastly different ecosystems, continuous reflectance data and a set of spectral indices associated with canopy leaf area and chlorophyll content were correlated well to CO2 flux parameters (e.g. NEP, GEE, etc.). These spectral parameters traced well the dynamics in vegetation carbon flux induced by the variations in temperature, nutrient and moisture availability. Our results suggest a strong correlation between CO2 flux and the indicators associated with pigment content (e.g. chlorophyll feature). These findings are compared to simulations of results expected to be obtained from the Landsat-8 and Sentinel-2 visible/near-infrared and short-wave infrared data. Imaging spectrometry provided high spatial distribution maps of CO2 fluxes absorbed by the vegetation. The bio-indicators with strongest relationships to NEP were calculated using continuous spectra, using numerous wavelengths associated with chlorophyll content and/or derivative parameters. Common (global) spectral approach to trace vegetation function and estimate it’s CO2 sequestration ability is feasible. It requires a diverse spectral coverage representative of the major ecosystem types, and spectral time series covering the dynamics within a cover type.