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Land surface temperature (LST) retrievals obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) are of considerable importance for climatic research. However, the accurate evaluation of LST from space has been severely limited because of the difficulty in separating atmospheric from surface effects as the surface cannot be modeled as a black-body radiator. With this goal in mind, a novel extension of the split-window technique is presented in which the atmospheric contribution to the radiance measured by the satellite is investigated by the ratioing of covariance and variance of the brightness temperatures measured in Channels 4 and 5 of AVHRR/2. Furthermore, the contribution of emissivity is evaluated from coefficients that depend on the spectral emissivities in both thermal channels. Using a wide range of simulations from an atmospheric radiative transfer model it is shown that the proposed algorithm provides an estimate of LST, to within 0.4 K if the spectral surface emissivity is known, which is better than that given by the currently used split-window algorithms for LST determination. Also the limitations on algorithm accuracy are discussed considering different values of noise equivalent temperature. Finally we present the preliminary results obtained using the proposed method from AVHRR data over a semi-arid region of Northwestern Victoria in Australia provided by CSIRO, and a mountainous region of Northeast of France acquired in the frame of Regio Klimat Projekt.