Spatial representativeness of flux footprints at pixel scales over mountainous ecosystems
With the availability of remote sensing images since the 1970s,the spatial-temporal continuum observations of the land surface can be obtained at the global scale.In this manner,remote sensing is an important information source for the large-scale estimation of land surface carbon,water,and energy fluxes.Global eddy covariance flux datasets are widely used to evaluate and produce remote sensing flux products.Given that tower-based fluxes can only represent the small areas around the tower,a mismatch usually occurs between the tower-based fluxes and multiscale pixels of remote sensing.Thus,the spatial representativeness of flux footprints must be evaluated at multiscale pixels.In this study,we choose the Wanglang Mountain Remote Sensing Field Observation and Research Station of Sichuan Province,a typical mountainous ecosystem of Southwest China,as the study area.This study used a two-dimensional parametric footprint model(flux footprint prediction,FFP)to characterize the spatiotemporal variations and analyze the spatial representativeness of flux footprints at multiscale pixels(i.e.,30,60,120,250,500,1000,1500,and 2000 m).In this work,the land cover types and normalized difference vegetation index were used to characterize the spatial representativeness of footprint among vegetation types and vegetation density at multiscale pixels,respectively.At the same time,two site-level simple representativeness indices for land cover type and vegetation density were proposed to evaluate the footprint-to-pixel representativeness across flux towers at Wanglang station.Results showed that the footprint fetch varied across flux towers at Wanglang station(10-103 m),and the footprints at multiple temporal resolutions had a low symmetry(usually less than 40％).For the temporal variations of footprints,the overlap of footprints had evident changes at the daily scale(0％-88％),and the variations were reduced at the monthly scale(usually larger than 83％).As for the three flux towers around Wanglang station,results showed that the station of deciduous broadleaf shrub(with observed height at 10 m),deciduous broadleaf forest(with observed height at 30 m),and evergreen needleleaf forest(with observed height at 75 m)had the optimal spatial representativeness at the pixel scales of 30,60,and 1000 m,respectively.Moreover,compared with vegetation density,the discrepancies of spatial representativeness were more evident for vegetation cover.The spatial representativeness differences of footprints must be paid attention to while validating remote sensing models and producing flux datasets around mountainous ecosystems.Moreover,the corresponding footprints must be combined with tower-based observations to characterize the temporal variations of fluxes when modeling and producing flux products at high temporal resolution(e.g.,daily scale).Given that the high spatial representativeness of footprints was limited to the pixels at high(a lower tower)and medium-low(a higher tower)spatial resolution,the estimation of ecosystem parameters and flux research over mountainous areas could be promoted by cognizing the spatial representativeness of footprint at pixel scales and combining the multiscale remote sensing observations with the spatial and temporal scaling method.
万方数据
维普
