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Earth Resources Observation and Science (EROS) |
Remote Sensing and Modeling Carbon FluxesOverview
Much of this work has been accomplished as part of the USAID GL-CRSP project "Livestock Development and Rangeland Conservation Tools for Central Asia (LDRCT)" Grant No. PCE-G-00-98-00036-00 to University of California, Davis. This project focused on the Central Asian countries of Kazakhstan, Uzbekistan, and Turkmenistan. The project focus was on broad livestock development issues such as animal production, socio-economic conditions, GIS technologies, resource availability, range forage, and carbon flux. The range forage and carbon flux component of this project included the scaling-up of flux tower measurements to the regional scale in a collaborative effort by the US Geological Survey, the USDA Agricultural Research Service (http://www.usu.edu/forage/frrl.htm), University of California, Davis, host country institutions, the Office of Agriculture and Food Security, Global Bureau, US Agency for International Development (under Grant No. PCE-G-98-00036-00) The opinions expressed herein are those of the authors and do not necessarily reflect the views of USAID, UC Davis, USDA ARS, or USGS. USGS/EROS has created and validated models that employ near-real-time remotely sensed data, spatial data regarding soil attributes and land management, and the biophysical mechanisms that account for carbon fluxes between the land surface and the atmosphere. Using these models, quantitative maps are created for the seasonal and annual dynamics of net ecosystem exchange (NEE) of carbon. The models can be manipulated to explore carbon fluxes at regional and national scales. Much of this research has focused on carbon flux in grasslands. Grassland ecosystems (rangelands) store most
of their carbon below ground. Because rangelands constitute 40% of the Earth's terrestrial surface,
they could be a significant factor in the global carbon budget. To assess the role of rangelands
in the global carbon cycle, the exchange of CO2 between rangelands and the atmosphere must be quantified. A method for quantifying CO2 fluxes between
rangeland soils and plants and the atmosphere involves the use of flux towers. These instruments measure
the vertical changes in atmospheric CO2 concentrations, along with wind speed and direction
above the vegetation over a distance upwind (fetch) that is about one hundred times the height of CO2
sensors. In order to quantify CO2 fluxes over large expanses of rangeland, it is necessary to
extrapolate data gathered from one or a few flux towers to entire regions or ecosystems. In doing so,
it is also necessary to consider variability in climate, soils, and management conditions that often
occur in rangelands. Remote sensing provides a feasible and economical means to estimate the spatial
and temporal dynamics of CO2 flux in rangelands. Vegetation indices derived from remotely
sensed data, such as the Normalized Difference Vegetation Index (NDVI), have been correlated with
CO2 fluxes.
Remote Sensing Models to Quantify Performance Anomalies in Grasslands and Steppes
The Bowen ratio/energy balance technique (BREB) was used to continuously monitor CO2 at a sagebrush steppe site near Dubois, Idaho. Mathematical modeling of CO2 fluxes was done to fill gaps resulting from missing or aberrant data. Thus, daily integrals across the entire growing season were quantified. Results of this research suggested that a combination of BREB measurements and modeling techniques can be used to estimate CO2 fluxes on important rangeland ecosystems.
As a 'Proof of Concept' to correlate remote sensing and flux tower data, a strong relationship between AVHRR NDVI (1 km resolution) and daytime CO2 fluxes was demonstrated at the Dubois site, and was found to be fairly consistent across four growing seasons (1996-1999) during both drought and wet years.
Calibration of Remotely Sensed, Coarse Resolution NDVI to CO2 Fluxes in a Sagebrush-Steppe Ecosystem
To improve the utility of flux tower data, daytime net ecosystem CO2 exchange was partitioned into fluxes due to respiration and gross primary productivity (GPP). This was done by Tagir Gilmanov using complex, light-curve equation fitting. The resulting separation of CO2 flux data provided very useful information on these fundamental processes, which are difficult to quantify with classical measurement techniques. This technique was first applied to data collected from a flux tower in Central Asia.
A Method to Estimate Gross Primary Productivity from Bowen Ratio-Energy Balance CO2 Flux Measurements and Construction of Predictive Relationships between NDVI and CO2 Flux and later to flux towers in the United States:
Gross Primary Production and Light Response Parameters of Four Southern Plains Ecosystems Estimated using Long-Term CO2-Flux Tower Measurements
Remotely sensed vegetation indices provide a temporally and spatially dynamic variable that is a key for the mapping of CO2 fluxes. NDVI, which was found to be a surrogate for photosynthetic potential, was expected to be more strongly correlated to GPP than the daytime net CO2 fluxes as demonstrated in the study on a sagebrush steppe at Dubois, Idaho. The correlation between 1-km NDVI and flux tower data, together with the quantification of ecosystem respiration and GPP, was first employed in measurements obtained from Central Asia. LDRCT has been operating Bowen ratio energy-balance (BREB) flux towers in the Central Asian nations of Turkmenistan, Uzbekistan, and Kazakhstan (one flux tower per country) since 1998.
For further International activities please visit http://edcintl.cr.usgs.gov/. Remote Sensing and Geographic Information System in Rangelands of Northern Kazakhstan: Quantification and Mapping of Seasonal CO2 Fluxes from Bowen Ratio-Energy Balance Measurements Gross Primary Productivity of the True Steppe in Central Asia in Relation to NDVI: Scaling up CO2 Flux Measurements Scaling Up of Carbon Fluxes to Predict the Carbon Dynamics in Kazakhstan Central Asia
The USDA Agricultural Research Service (ARS) has been monitoring rangeland CO2 fluxes across
the western United States since 1996 using a network of flux towers. Based on the success of the Central
Asian scaling-up of flux tower measurements, the GL CRSP intiated a collaborative effort among USAID, ARS,
South Dakota State University, University of California at Davis, Utah State University, and EROS to spatially
extrapolate CO2 fluxes from the USDA ARS Rangeland (AgriFlux) Network and selected towers from the
AmeriFlux Network. This synergistic use of flux tower data sets for validation and alogithm development focused
on improving scaling up algorithm accuracy and robustness in both Central Asia and the Western U.S.
This project, the "ARS-CRSP CO2 Flux Scaling Project", was supported by funding from
USAID-GL CRSP, USDA ARS Agriflux participants, USDA Global
Change Program, and the USGS.
This project has demonstrated the complementary nature of domestic and international projects: Central Asian and North American data sets have been pooled together to develop more robust CO2 flux algorithms, and this work may lead to monitoring of rangeland fluxes throughout the Northern Hemisphere, and ultimately, worldwide. Gross Primary Production and Light Response Parameters of Four Southern Plains Ecosystems Estimated Using Long-Term CO2 Flux Tower Measurements Scaling-Up Tower CO2 Fluxes in Semi-Arid Grasslands of the Great Plains Using Spectral Vegetation Indices and Phenomenological Modeling Poster Modeling and Mapping of Carbon Fluxes in Rangeland Ecosystems
Quantifying Regional Range Condition for Erosion and Carbon Modeling
Evaluation of the Empirical Piecewise Regression Model in Simulating GPP in the Northern Great Plains
The USGS Earth Resources Observation & Science (EROS) and the National Oceanic and Atmospheric Administration (NOAA) in collaboration with South Dakota EPSCoR Center for Biocomplexity Studies, South Dakota State University (SDSU), South Dakota School of Mines and Technology (SDSM&T), and Augustana College have begun work with a carbon flux tower in eastern South Dakota. The tower is part of the paired plot analysis being conducted on two separate grazed grassland sites in South Dakota. The work stems from the proposal, Quantification and scaling-up of the coupled biogeochemical cycles of carbon and water in grassland ecosystems of South Dakota: Synthesis of flux tower measurements, modeling, GIS, and remote sensing, funded through the South Dakota EPSCoR Center for Biocomplexity Studies. The study seeks to quantitatively characterize diurnal, seasonal and year-to-year dynamics of carbon and water fluxes in grazed grasslands of South Dakota using eddy covariance flux tower measurements, refine the use of remote sensing to quantify these fluxes, and quantitatively characterize the carbon pools using on-site biomass measurements and application of carbon isotope discrimination techniques in pastures at different range conditions classes. A paired-plot analysis will be used to evaluate environmental driving factors and quantify magnitudes and variability of CO2 and H2O fluxes by comparison measurements at the two sites. Those involved in the proposal are as follows:
Please refer to http://edc.usgs.gov/calval/ for more information regarding USGS Earth Resources Observation & Science (EROS) Instrumentation. Return to Top
A Soil Climate Analysis Network (SCAN) tower has been placed at the USGS Earth Resources Observation & Science (EROS) Campus by the USDA Natural Resources Conservation Service. It monitors environmental variables and soil moisture at numerous depths. This data can be downloaded at ftp://ftp.wcc.nrcs.usda.gov/data/scan/sd/2072.
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