Use of remotely sensed land use classification for a better evaluation of micrometeorological flux measurement sites

摘要

Long-term flux measurement sites are often characterized by a heterogeneous terrain, which disagrees with the fundamental theoretical assumptions for eddy-covariance measurements. An evaluation procedure to assess the influence of terrain heterogeneity on the data quality has been developed by Gockede et al. (2004), which combines existing quality assessment tools for flux measurements with analytic footprint modeling. In addition to micro-meteorological input data, this approach requires information defining the land use structure and the roughness of the surrounding terrain. The aim of this study was to improve the footprint based site evaluation approach by using high-resolution land use maps derived by Landsat ETM+ and ASTER satellite data. The influence of the grid resolution of the maps on the results was examined, and four different roughness length classification schemes were tested. Due to numerical instabilities of the analytic footprint routine, as an additional footprint model a Lagrangian stochastic footprint routine (Rannik et al., 2003) was employed. Application of the approach on two German FLUXNET sites revealed only weak influence of the characteristics of the land use data when the land use structure was homogeneous. For a more heterogeneous site, use of the more detailed land use maps derived by remote sensing methods resulted in distinct differences indicating the potential of remote sensing for improving the flux measurement site evaluation.