@article {KNZ001211,
	title = {Assessing the multi-resolution information content of remotely sensed    variables and elevation for evapotranspiration in a tall-grass prairie    environment},
	journal = {Remote Sensing of Environment},
	volume = {112},
	year = {2008},
	pages = {2977 -2987},
	abstract = {<p>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.</p>},
	keywords = {LTER-KNZ, Entropy, information theory, Konza Prairie, Latent heat, MODIS, Spatial heterogeneity, SVAT model, wavelets},
	doi = {10.1016/j.rse.2008.02.002},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0034425708000655?via\%3Dihub},
	author = {N. Brunsell and J.M. Ham and Owensby, C.E.}
}
