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TitleExtending aircraft and tower-based CO2 Flux measurements to a boreal region using a Landsat TM land cover map
AuthorChen, J M; Leblanc, S GORCID logo; Cihlar, J; Desjardins, R; MacPherson, J
SourceJournal of Geophysical Research, Atmospheres vol. 104, issue 14, 1999., Open Access logo Open Access
Alt SeriesEarth Sciences Sector, Contribution Series 20042594
Mediapaper; on-line; digital
File formatpdf
AreaPrince Albert
Lat/Long WENS-106.0000 -104.5000 54.0000 53.0000
SubjectsScience and Technology; Nature and Environment; remote sensing; vegetation; LANDSAT imagery; carbon dioxide; ecosystems; heat flow; modelling
Illustrationsgraphs; satellite images; tables; histograms
Released1999 07 01
AbstractThere has been an increasing need to measure the exchange of CO2between the atmosphere and vegetated surfaces for large areas in order to quantify the carbon budget of terrestrial biosphere. The boreal landscape is strongly heterogeneous due to different forest cover types and disturbance regimes, and regional quantification of CO2 flux is difficult without numerous species-specific flux measurements. During the BOReal Ecosystem Atmosphere Study (BOREAS) in 1994 and 1996, the National Research Council of Canada (NRC) and agriculture Canada operated a Twin-Otter aircraft that measured CO2, sensible and latent heat fluxes and other trace gases over boreal forests in Saskatchewan, Canada. A flux-unmixing method was developed to calculate flux densities for eight major cover types from the aircraft based measurements. Using a co-registered landcover map at 30 m resolution derived from Landsat Thematic Mapper data, the contribution of each cover type to the CO2 flux measured by the aircraft was estimated using a contributing area (footprint) function according to the wind direction, the atmospheric stability, the horizontal distance of each pixel from the aircraft, and aircraft height. The unmixing method uses a linear inversion method with the footprint-weighted cover type fractions as the set coefficients for each segment of a flight line. In the inversion, various constraint strategies were used to confine the inversion results to minimise the effect of various sampling errors. It is shown that: (1) mathematical constraint is critically important in the inversion, (2) a simple constraint toward the mean flux values is effective in producing reasonable accurate inversion results, and (3) the inversion accuracy can be further improved when simultaneous tower measurements in the dominant cover types are used as tight constraints. With such constraints, the flux from the cover types without tower measurements were reliably estimated. It is concluded that aircraft measurement adds to our ability to map regional flux field using remote sensing images because (1) it allows the derivation of flux data for cover types without tower-based measurements, and (2) is can be used to infer the representativeness of tower measurements for the measured cover types in the landscape.

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