Assessing the spatial representativeness of eddy-covariance measurements of AmeriFlux network based on remote sensing and footprint analysis

Abstract:

The eddy-covariance towers of AmeriFlux network are important for the analysis of terrestrial ecosystem-atmosphere interactions, and they have been used to improve our understanding of the mechanism behind terrestrial carbon cycle and upscaling from site to landscape and regional scales. However, the spatial representativeness of AmeriFlux network has not been assessed, especially accounting for the effects of land cover change on it using high spatial resolution data. Here we demonstrated an approach for evaluating the spatial representativeness of flux tower measurements based on footprint climatology analyses, land cover change data and remotely sensed vegetation indices. This method was applied to 79 flux towers of AmeriFlux network located in the continental United States, covering evergreen forest, deciduous forest, mixed forest, grass, cropland, shrub, and wetland biomes. For each site, monthly and annual footprint climatologies (i.e. monthly or annual accumulative footprints) were calculated using the Simple Analytical Footprint model on Eulerian coordinates (SAFE-f). The footprint climatologies were then overlaid on the images of Normalized Difference Vegetation Index (NDVI) and National Land Cover Database (NLCD) for the years (2001, 2006 and 2011), which were used as surrogates of land surface fluxes to assess the spatial representativeness. For most sites of AmeriFlux network, the results show that (i) the percentages of the target vegetation functional type (dominant land cover) observed by the AmeriFlux towers were higher than 60%; (ii) to some extent, most of the AmeriFlux sites presented anisotropically distributed patterns of NDVI within the 90% annual footprint climatology area; (iii) the land surface heterogeneity within the flux footprint area differed among sites; and (iv) the land cover types had changed higher than 10% within 6 km*6 km area centered at the flux tower for 5 AmeriFlux sites. We conclude that the footprint modeling based on high spatial resolution remotely-sensed data is a pragmatic approach for assessing the spatial representativeness of flux tower measurements. Meanwhile, the land cover change within footprint climatology area may affect the upscaling of eddy-covariance flux measurement to landscape/regional scales.