EO-1 Hyperion spectral time series for remote sensing of vegetation function and carbon flux dynamics

Petya Krasteva Entcheva Campbell, NASA GSFC/JCET/UMBC, petya.campbell@nasa.gov (Presenter)
Elizabeth M. Middleton, NASA GSFC, elizabeth.m.middleton@nasa.gov
Karl Fred Huemmrich, NASA GSFC/UMBC, karl.f.huemmrich@nasa.gov
Sergio Bernardes, NASA, sbernard@uga.edu
Qingyuan Zhang, GESTAR/USRA, qingyuan.zhang-1@nasa.gov
Lawrence Ong, NASA SSIA, lawrence.ong@nasa.gov

Spatial heterogeneity and seasonal dynamics in vegetation physiology contribute significantly to the uncertainties in regional and global CO2 budgets. High spectral resolution imaging spectroscopy (~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. Since 2008 the EO-1 mission has targeted the collection of time series for vegetation studies, and currently time series of hyperspectral images are available for studies of vegetation carbon dynamics at a number of FLUX sites, as demonstrated by the table below.

EO-1 Hyperion seasonal composites were assembled and the radiance data were corrected for atmospheric effects and converted to surface reflectance using the Atmosphere CORrection Now (ACORN) model [2]. Spectral differences and seasonal trends were evaluated for each vegetation type and site specific phenology. 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). Comparing spectral parameters in these very different ecosystems, continuous reflectance data and a set of spectral parameters were correlated well to CO2 flux parameters (e.g., NEP, GEP, etc.). These spectral parameters traced well the dynamics in vegetation carbon flux induced by the variations in temperature, nutrient and moisture availability. Imaging spectrometry provided high spatial resolution maps of CO2 fluxes absorbed by vegetation, and proved to be efficient in tracing seasonal flux dynamics.

The study illustrates the ability of Earth Observing-1 (EO-1) Hyperion images to map CO2 flux dynamics, using examples for Mongu, Zambia but similar results have been obtained for deciduous and confer forest and grasslands. The research is being expanded further to include northern hardwood forest, evergreen coniferous forest, savanna, woodland and rain forest at additional sites with available FLUXNET data and EO-1 Hyperion time series.

Our results suggest a strong correlation between CO2 flux and Hyperion's spectral bio-indicators associated with chlorophyll content. The bio-indicators with strongest relationships to NEP were derived using continuous spectra or numerous wavelengths associated with chlorophyll content. We verified the feasibility of a common (global) hyperspectral strategy to monitor vegetation processes, including the vegetation ability to uptake CO2. The approach requires a diverse spectral coverage, representative of major ecosystem types, as well as time series of spectra representing the internal dynamics of cover types.

Our findings demonstrate the ability of satellite imaging spectrometers to capture key vegetation bio-physical parameters and accurately monitor the dynamics in vegetation function. They are directly relevant to the forthcoming HyspIRI (NASA, USA) and EnMAP (DLR, Germany) hyperspectral missions and in future work we will assess the relevance of the results to the Sustainable Land Imaging initiative (NASA, USA), the long term time series of Landsat 8 and the forthcoming Sentinel-2 (ESA) and VENμS (France/Israel) missions.

Presentation: 2015_Poster_Campbell_234_102.pdf (2459k)

Presentation Type:  Poster

Session:  Theme 3: Future research direction and priorities: perspectives relevant to the next decadal survey   (Mon 4:30 PM)

Associated Project(s): 

• Campbell, Petya: Assessing ecosystem diversity and urban boundaries using surface reflectance and emissivity at varying spectral and spatial scales ...details
• Middleton, Betsy: Spectral Bio-Indicators of Ecosystem Photosynthetic Efficiency II: Synthesis and Integration ...details

Poster Location ID: 234