TY - JOUR T1 - Assessing the multi-resolution information content of remotely sensed variables and elevation for evapotranspiration in a tall-grass prairie environment JF - Remote Sensing of Environment Y1 - 2008 A1 - N. Brunsell A1 - J.M. Ham A1 - Owensby, C.E. KW - Entropy KW - information theory KW - Konza Prairie KW - Latent heat KW - MODIS KW - Spatial heterogeneity KW - SVAT model KW - wavelets AB -
Understanding the spatial scaling behavior of evapotranspiration and its relation to controlling factors on the land surface is necessary to accurately estimate regional water cycling. We propose a method for ascertaining this scaling behavior via a combination of wavelet multi-resolution analysis and information theory metrics. Using a physically-based modeling framework, we are able to compute spatially distributed latent heat fluxes over the tall-grass prairie in North-central Kansas for August 8, 2005. Comparison with three eddy-covariance stations and a large aperture scintillometer demonstrates good agreement, and thus give confidence in the modeled fluxes. Results indicate that the spatial variability in radiometric temperature (a proxy for soil moisture) most closely controls the spatial variability in evapotranspiration. Small scale variability in the water flux can be ascribed to the small scale spatial variance in the fractional vegetation. In addition, correlation analysis indicates general scale invariance and that low spatial resolution data may be adequate for accurately determining water cycling in prairie ecosystems.
VL - 112 UR - https://www.sciencedirect.com/science/article/abs/pii/S0034425708000655?via%3Dihub ER -