Ground-based measurements of land-surface temperature (LST) performed in a homogeneous site of rice crops close to Valencia, Spain, were used for the validation of the calibration and the atmospheric correction of the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) thermal band. Atmospheric radiosondes were launched at the test site around the satellite overpasses. Field-emissivity measurements of the near-full-vegetated rice crops were also performed. Seven concurrences of Landsat-7 and ground data were obtained in July and August 2004-2007. The ground measurements were used with the MODTRAN-4 radiative transfer model to simulate at-sensor radiances and brightness temperatures, which were compared with the calibrated ETM+ observations over the test site. For the cases analyzed here, the differences between the simulated and ETM+ brightness temperatures show an average bias of 0.6 K and a rootmean-square difference (rmsd) of ±0.8 K. The ground-based measurements were also used for the validation of LSTs derived from ETM+ at-sensor radiances with atmospheric correction calculated from the following: 1) the local-radiosonde profiles and 2) the operational atmospheric-correction tool available at http://atmcorr.gsfc.nasa.gov. For the first case, the differences between the ground and satellite LSTs ranged from -0.6 to 1.4 K, with a mean bias of 0.7 K and an rmsd = ±1.0 K. For the second case, the differences ranged between -1.8 and 1.3 K, with a zero average bias and an rmsd = ±1.1 K. Although the validation cases are few and limited to one land cover at morning and summer, results show the good LST accuracy that can be achieved with ETM+ thermal data.

A database of global, cloud-free, and atmospheric radiosounding profiles was compiled with the aim of simulating radiometric measurements from satellite-borne sensors in the thermal infrared. The objective of the simulated data is to generate split-window (SW) and dual-angle (DA) algorithms for the retrieval of land surface temperature (LST) from Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) and Envisat/Advanced Along Track Scanning Radiometer (AATSR) data. The database contains 382 radiosounding profiles acquired over land, with nearly uniform distribution of precipitable water between 0.02 and 5.5 cm. Radiative transfer calculations were performed with the MODTRAN 4 code for six viewing angles between 0deg and 60deg. The resulting radiance spectra were convoluted with the response filter functions of MODIS bands 31 and 32 and AATSR channels at 11 and 12 mum. By using the simulation database, the SW algorithms adapted for MODIS and AATSR data and the DA algorithms for AATSR data were developed. Both types of algorithms are quadratic in the brightness temperature difference and depend explicitly on the land surface emissivity. The SW and DA algorithms were validated with actual ground measurements of LST collected concurrently to MODIS and AATSR observations in a site located close to the city of Valencia, Spain, in a large, flat, and thermally homogeneous area of rice crops. The results obtained have no bias and a standard deviation around plusmn0.5 K for the SW algorithms at nadir for both sensors. The SW algorithm used in the forward view results in a bias of 0.6 K and a standard deviation of plusmn0.8 K. The worst results are obtained in the other algorithms with a bias close to -1.0 K and a standard deviation close to plusmn1.1 K in the case of the DA algorithms.