Remote sensing technology has undeniable importance in various industrial applications. Some of which include mineral exploration, plant detection, defect detection in aerospace and shipbuilding, and optical gas imaging, to name a few. Remote sensing technology has been continuously evolving, offering a range of image types that can facilitate the aforementioned applications. One such type is Hyperspectral Images (HSIs). Unlike multispectral and natural images, HSIs consist of hundreds of bands, which makes it easier to identify objects through their spectral reflectance signals. Despite its high spectral resolution, HSIs suffer from low spatial resolution. This is a natural tradeoff that occurs due to cameras attempting to capture 3D images using 2D sensors. In order to implement remote sensing applications effectively with satisfying accuracy, HSIs need to have high spectral resolution as well as high spatial resolution. This webinar discusses the several advances in the field of HSI spatial enhancement, highlights and assesses the most recent state-of-the-art approaches, and draws the future direction of this research field.