A split-window algorithm for land surface temperature from advanced very high resolution radiometer data: Validation and algorithm comparison

Abstract

A split-window algorithm for deriving land surface temperatures (LSTs) from advanced very high resolution radiometer (AVHRR) channels 4 and 5 is proposed and validated with in situ measured temperatures. On the basis of the radiative transfer theory the algorithm defines a set of surface-independent coefficients which are equivalent to the classical split-window coefficients for sea surface temperature (SST). These coefficients are calculated using SST matchups (coincident AVHRR and buoy measurements) provided by the National Oceanic and Atmospheric Administration (NOAA)-NASA Pathfinder Database of worldwide measurements. Thus calibration of the split-window coefficients is done using real data. The variability of atmospheric attenuation is represented in the proposed algorithm by a quadratic dependence on the brightness temperature difference. For LST determination the emissivity effect is modeled through an additive coefficient which depends on surface emissivity in the AVHRR channels 4 and 5. The algorithm is validated for both SST and LST by using independent ground-based and AVHRR data. The database used in the validation of LST was obtained for a wide range of surface types in a semiarid environment. The same databases are used to compare the accuracies of other published split-window algorithms. The proposed algorithm yields standard errors of temperature estimate between ±1.0 and ±1.5 K, and no significant biases are observed. Although results are encouraging, more validation is required principally for moist atmospheric conditions.