Interpolation and combination rules for the temporal and spatial enhancement of SEVIRI and MODIS thermal image sequences

Brightness temperature (BT) images acquired via satellite platforms are at the core of Earth Observation applications, aiding activities such as agriculture, forestry, and urbanization management. However, said applications may suffer from limitations on the spatial resolution and/or acquisition rate of image sequences. Indeed, due to physical constraints on the sensing devices and on the orbiting platforms, the information is typically sparse in either space or time. This problem can be faced through data fusion techniques that yield improved synthetic images by taking advantage of multisensor data. In this work, we address the specific issue of enhancing image sequences through deterministic interpolation and combination procedures. We assume that an high temporal resolution/low spatial resolution (htr/LSR) sequence is available along with a low temporal resolution/high spatial resolution (ltr/HSR) and propose an approach to obtain an htr/HSR sequence consisting in three steps: (i) spatially interpolating the htr/LSR sequence; (ii) temporally interpolating the ltr/HSR sequence; and (iii) combining the two intermediate sequences. We consider and assess comparatively several options to carry out the three steps on thermal infrared images acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors acting as the htr/LSR and the ltr/HSR sequence, respectively.