The definitive version is available at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973This paper describes two approaches for estimating sensible heat flux, using surface renewal and similarity concepts. One approach depends on a temperature structure function parameter and is valid in the inertial sub-layer. The other approach depends on the temperature standard deviation and operates when measurements are made above the canopy top, either in the roughness or inertial sub-layer. The approaches were tested over turf grass, rangeland grass, wheat, grape vineyard and nectarine and olive orchards. It is shown that the free convection limit expression for the standard deviation method holds for slightly unstable conditions. When surface homogeneity and fetch requirements are not fully met in the field, the results show that the equations based on surface renewal principles are more robust and accurate than equations exclusively based on similarity backgrounds. It is likely that the two methods require no calibration unless the canopy is heterogeneous. Under unstable conditions, the free convection limit equation, which depends on the temperature standard deviation, can provide on-line sensible heat flux density estimates using affordable battery-powered data logger with temperature data as the only input. The approach performed well when measuring near or well above the canopy top, thus, suggesting that the method is useful for long term monitoring over growing vegetation.This work was supported by the Ministerio de Ciencia y Tecnología under the Spanish project REN2001-1630 CLI, the DURSI of the Generalitat of Catalunya and the University of Lleida. Data from the grassland was supported by grants from the US Dept of Energy and the California Agricultural Experiment Station.Peer reviewed