Hostname: page-component-848d4c4894-2pzkn Total loading time: 0 Render date: 2024-06-02T16:50:52.682Z Has data issue: false hasContentIssue false

Relating CO2 fluxes to spectral vegetation indices in tundra landscapes: importance of footprint definition

Published online by Cambridge University Press:  27 October 2009

A.S. Hope
Affiliation:
Department of Geography, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4493, USA
J.B. Fleming
Affiliation:
Department of Geography, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4493, USA
G. Vourlitis
Affiliation:
Department of Biology, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4614, USA
D.A. Stow
Affiliation:
Department of Geography, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4493, USA
W.C. Oechel
Affiliation:
Department of Biology, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4614, USA
T. Hack
Affiliation:
Department of Geography, San Diego State University, 5300 Campanile Drive, San Diego, CA 92182-4493, USA

Abstract

Carbon flux measurements made at an elevated point are associated with an effective upwind area or ‘footprint.’ Since Arctic tundra landscapes can exhibit substantial heterogeneity within the footprint of an eddy correlation tower, it may be necessary to determine the relative point source contributions to the observed flux if landscape properties are to be related to the flux. This study evaluates the potential importance of representing footprint source contributions in relationships that are developed between tower observations of net ecosystem exchange of carbon dioxide (NEE) and a remotely sensed spectral vegetation index. Satellite data collected over the foothills region of the North Slope of Alaska are used to determine spatial patterns of a spectral vegetation index in the calculated footprints of 30 randomly selected tower locations. A previously developed relationship between NEE and the vegetation index is used to calculate NEE at each tower location using two techniques, one that explicitly considers the footprint pattern of relative contributions to tower fluxes and another that ignores these patterns. The results indicate that if carbon fluxes measured at a tower are to be related to remotely sensed spectral vegetation indices, then it is necessary to consider the relative flux contributions from within the tower footprints for sites on the North Slope of Alaska.

Type
Articles
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Chavez, J.P.S. 1988. An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24: 459479.CrossRefGoogle Scholar
Fitzjarrald, D.R., and Moore, K.E.. 1992. Turbulent transports over tundra. Journal of Geophysical Research 97 (D15): 16, 717–16, 729.CrossRefGoogle Scholar
Leclerc, M. Y., and G.W., Thurtell. 1990. Footprint prediction of scalar fluxes using a Markovian analysis. Boundary-Layer Meteorology 52: 247258.CrossRefGoogle Scholar
Manabe, S., and Wetherald, R.T.. 1987. Large-scale changes of soil wetness induced by an increase in atmospheric carbon dioxide. Journal of Atmospheric Science 44: 12111235.2.0.CO;2>CrossRefGoogle Scholar
Oechel, W.C., Hastings, S.J., Vourlitis, G., Jenkins, M., Riechers, G., and Grulke, N.. 1993. Recent change of Arctic tundra ecosystems from net carbon dioxide sink to source. Nature 361: 520523.CrossRefGoogle Scholar
Rastetter, E.B., King, A.W., Cosby, B.J., Hornberger, G.M., O'Neill, R.V., and Hobbie, J.E.. 1992. Aggregating fine scale ecological knowledge to model coarser-scale attributes of ecosystems. Ecological Applications 2(1): 5570.CrossRefGoogle ScholarPubMed
Schuepp, P.H., Leclerc, M.Y., MacPherson, J.I., and Desjardins, R.L.. 1990. Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation. Boundary-Layer Meteorology 50: 355373.CrossRefGoogle Scholar
Stow, D.A., Burns, B., and Hope, A.S.. 1993. Spectral, spatial and temporal characteristics of Arctic tundra reflectance. International Journal of Remote Sensing 14 (13): 24452462.CrossRefGoogle Scholar
Walker, D.A., Binnian, E., Evans, B.M., Lederer, N.D., Nordstrand, E., and Webber, P.C.. 1989. Terrain, vegetation and landscape evolution of the R4D research site, Brooks Range foothills, Alaska. Holarctic Ecology 2: 238261.Google Scholar
Whiting, G.J., Bartlett, D.S., Fan, S., Bakwin, P.S., and Wofsey, S.C.. 1992. Biosphere/atmosphere CO2 exchange in tundra ecosystems: community characteristics and relationships with multispectral surface reflectance. Journal of Geophysical Research 97(D15): 16, 671–16, 680.CrossRefGoogle Scholar
Wilson, C.A., and Mitchell, F.B.. 1987. A doubled CO2 climate sensitivity experiment with a GCM including a simple ocean. Journal of Geophysical Research 92: 13, 315–13, 343.CrossRefGoogle Scholar