Downscaling Landsat 7 ETM+ thermal imagery using land surface temperature and NDVI images

Thermal infrared (TIR) satellite images and derived land surface temperature (LST) are variables of great interest in many remote sensing applications. However, the TIR band has a spatial resolution which is coarser than the other multispectral bands for a given satellite sensor (visible, near and shortwave infrared bands); therefore, the spatial resolution of the retrieved LST from available satellite-borne sensors is not accurate enough to be used in certain applications.The application of a method is shown here for obtaining LST images with enhanced spatial resolution using the LST at a coarser resolution and the Normalized Difference Vegetation Index (NDVI) of the same scene using Downscaling Cokriging (DCK). A LST image with perfect coherence was obtained by applying this method to a Landsat 7 ETM+ image. This implies that, if the downscaled LST image is degraded to its original resolution, the degraded image obtained is identical to the original. Hence high spatial resolution LST images were obtained without altering the original radiometry with the inclusion of artefacts. Moreover, the performance of DCK was compared with global and local TSHARP methods. The RMSE of the sharpened images were 0.85, 0.92 and 1.1 K, respectively.

► We apply a method to obtain high spatial resolution (HR) land surface temperature (LST) images.
► We retrieve LR LST from the downscaled TIR band by the inversion of the radiative transfer equation.
► Downscaling Cokriging (DCK) is used to increase the spatial resolution of Landsat 7 ETM+ LR LST image.
► The downscaled LST image preserves the consistency of the original image radiometry.
► Optimum values of the fusion quality indexes, correlation coefficient, ERGAS and Q are obtained.