Service robotics and machine learning for close-range remote sensing

L'abstract è presente nell'allegato / the abstract is in the attachmen

Novel spectral imaging instrumentation for environmental sensing in extreme environments

Spectral imaging techniques provide a valuable means of improving our understanding of the world around us. Environmental monitoring approaches that utilise these techniques are, therefore, essential to our understanding of the effects of climate change. Hyperspectral imaging applications are of particular benefit to a broad range of environmental monitoring scenarios, providing rich datasets that combine both spectral and spatial information, enabling intricate features and variations to be visualised. However, to date, most commercially available hyperspectral instrumentation remains bulky and expensive, significantly limiting their user-base and accessibility. These factors substantially limit the use of these instruments resulting in much of our information coming from a few well-resourced research teams across a limited number of more easily accessed field locations. These limitations, have a compounded effect on the quality and robustness of hyperspectral data outputs, particularly within more extreme settings, as the comparatively small sample of more accessible locations is not necessarily representative of the much larger whole. This thesis presents on the development and testing of three novel low-cost hyperspectral imaging instruments designed specifically for environmental monitoring applications, providing valuable, low-cost alternatives to currently available commercial systems. Specifically, the three instruments presented within this thesis are: a low-cost laboratory-based hyperspectral imager, a semi-portable instrument capable of accurate data capture within a laboratory setting; the Hyperspectral Smartphone, an ultra-low-cost smartphone-based fully portable hyperspectral imager; and a low-cost high-resolution hyperspectral imager capable of resolving mm-scale spatial targets. All instruments were rigorously tested to analyse and evaluate their performances. Each instrument was shown to perform well across a range of environmental monitoring applications demonstrating that expensive commercial instrumentation is not required to achieve accurate and robust hyperspectral imaging. These low-cost instruments could promote the widespread dissemination of accessible hyperspectral imaging equipment, facilitating the democratisation of hyperspectral measurement modalities across environmental monitoring applications and beyond