Demonstrating the Suitability of the Radiance- Based Method for Assessing the Accuracy of MODIS Land Surface Temperature Products

Validation of satellite land surface temperature (LST) products is usually performed through direct comparison with ground-measured LSTs (temperature-based or T-b validation) and with the radiance-based (R-b) method where reference ground LSTs are obtained from at-sensor radiances, atmospheric temperature and water vapor profiles, and emissivity measurements. While T-b is the preferred method, it is only applicable to a few, single-component covers that are thermally homogeneous from the ground measurement scale (a few m) to the satellite scale (usually 1 km). The indirect R-b method is an alternative to extend the LST validation at a global scale over cover types where the T-b method is not feasible. In this study, we used ground LST measurements taken in a thermally homogeneous site coincident with moderate resolution imaging spectroradiometer (MODIS) Terra and Aqua overpasses (86 matchups) to assess the accuracy of the R-b LSTs derived from MODIS data. Mean bias (ground minus R-b LSTs) of −0.1 K and root mean square error (RMSE) of 0.8 K were obtained, showing good performance against ground measurements. Then, we apply operationally the R-b method for validating MODIS Level 2 LST products M*D11 and M*D21 over six test sites comprising a varied range of surfaces (4267 cases). The emissivity values necessary for the R-b calculations were obtained from 1) the M*D11 and M*D21 emissivity product and 2) an independently modeled emissivity using ground measurements and vegetation cover fraction estimates. For the M*D11 product, we obtained an overall bias (product minus R-b LST) of −0.5 K and RMSE of 0.9 K with either the product or the modeled emissivities. However, a significant difference was found between daytime and nighttime bias (−1.0 and 0.0 K, respectively). The daytime cold bias of M*D11 was attributed to an ill-tuning of the algorithm for high surface temperature and atmospheric humidity conditions. For the M*D21 product, the overall bias (RMSE) was 0.2 K (0.6 K) with the product emissivity, and 0.6 K (1.1 K) with the modeled emissivity, both in nighttime and daytime. These results compare well with recent studies and contribute to the global assessment of MODIS LST uncertainty.