Despite the tremendous number of landmines worldwide, existing methods for landmine detection still suffer from high scanning costs and times. Utilizing ubiquitous thermal infrared satellite imaging might potentially be an alternative low-cost method, relying on processing big image data collected over decades. In this paper we study this alternative, focusing on assessing the utility of resolution enhancement using state-of-the art super-resolution algorithms in landmine detection. The major challenge is the relatively limited number of thermal satellite images available for a given location, which makes the possible magnification factor extremely low for landmine detection. To facilitate the study, we generate equivalent satellite images for various landmine distributions. We then estimate the detection accuracy from a naive landmine detector on the super-resolution images. While our proposed methodology might not be useful for anti-personal landmines, the experimental results show a promising detection rates for large anti-tank landmines.