Mary Stuart is part of the team led by Dr. Willmott and she is a PhD student working on the development of novel spectral imaging instrumentation for environmental sensing applications in the Department of Electronic and Electrical Engineering at the University of Sheffield. They have recently released a paper called “Low-Cost Hyperspectral Imaging with A Smartphone” which demonstrates that high quality, portable hyperspectral imaging can be achieved at a fraction of the cost of currently available commercial instruments.
She shares some additional insights into this area of research, how their research will benefit the users of hyperspectral scanning and reveals why this field of research is of interest to her.
What is Hyperspectral imaging?
Hyperspectral imaging is an analytical technique that captures information from across the electromagnetic spectrum with the aim of identifying objects and materials within an image scene.
The significant benefit of hyperspectral imaging over other sensing techniques is that it captures both spatial and spectral information, creating a three dimensional ‘data cube’. This data cube contains two spatial dimensions that form the image of the scene, like a photograph, and one spectral dimension that shows the variations in illumination across each pixel of the image at each wavelength.
Different materials and objects within the image can then be identified from the data cube by identifying their unique spectral responses from the variations in illumination across the spectral dimension. Hyperspectral imaging is, therefore, a valuable technique that is used in a large variety of research areas, from medical applications to environmental monitoring.
Within environmental monitoring, which is my main area of focus, the range of application areas are extensive, with hyperspectral datasets being used across multiple different fields from vegetation monitoring, where hyperspectral imaging makes it possible to observe plant stress or potential pest outbreaks before they become visible to the naked eye, to examining water quality, where hyperspectral datasets can be used to monitor the quality of freshwater sources or to aid in the identification of potential pollution outbreaks.
What challenges within Hyperspectral imaging has your research overcome?
Currently available hyperspectral sensors are typically expensive, costing upwards of £30,000, and bulky, making them difficult to use in more remote locations. In our paper ‘Low-Cost Hyperspectral Imaging with a Smartphone’ we have challenged these limitations by developing a smartphone-based hyperspectral sensor for ca. £100.
The Hyperspectral Smartphone uses low-cost commercially available components and a three-dimensionally printed housing to create a simple attachment that can convert a standard smartphone camera into a visible wavelength hyperspectral sensor. It is a user-friendly, portable instrument that is accessible to anyone with a smartphone, providing a substantial increase in accessibility and an opportunity to capture high quality datasets with minimal costs and without the need for extensive training. The portability of this instrument means it can be applied to a wide range of application areas including more inaccessible field sites, making it easier to capture datasets that may otherwise have been infeasible.
With this instrument we have demonstrated the potential available in the field of smartphone-based hyperspectral imaging, providing a solid foundation for more accessible hyperspectral data collection which, in turn, provides an opportunity to gain a better understanding of the processes affecting, and changes taking place within, a wide range of environmental settings.
Will the use of smartphones open up more areas of use for hyperspectral scanning and if so what are these?
The introduction of smartphones to hyperspectral imaging applications provides a significant opportunity to improve the accessibility of this method of data collection. By improving the accessibility, related to both cost and portability, it makes it possible for hyperspectral instruments to be deployed in a wide variety of environmental settings, including those that are more remote or feature difficult terrain. Furthermore, the ubiquity of smartphones, and the low-cost of additional components, means that smartphone-based hyperspectral instruments can be easily accessed by a broad range of research groups and organisations.
This benefits more than just the immediate academic community as, by increasing the user base for these instruments it, in turn, increases the volume of data available to help us understand these environments which can help us to better understand the processes that are influencing change within these settings. To date, many hyperspectral field deployments have been limited to a few more easily accessed locations which restricts our understanding as one accessible location is not necessarily representative of the many that are more difficult to access. By minimising these restrictions to accessibility with smartphone-based instruments we help to provide a means of better understanding the factors affecting key environmental settings around the world and, in turn, how they may be affected by climate change.
What interests you about this area of research?
I find Hyperspectral imaging incredibly interesting. The wealth of information it can provide is remarkable, providing insights that cannot be observed with the naked eye. As a tool it can be applied to a multitude of application areas making it truly versatile, and it makes determining new applications an exciting prospect.
I have always been interested in the natural environment, and, as such, completed my undergraduate degree in environmental science before going on to complete a masters in glaciology. Through my PhD I’ve had the opportunity to combine my knowledge in environmental monitoring with hyperspectral imaging through the creation of novel instrumentation. I enjoy the process of developing instruments from initial ideas through to working devices. Being able to develop instruments that can help improve current data collection methods is something that I am particularly interested in. I feel this is especially relevant within the field of environmental monitoring, as the easier it is for us to understand the factors affecting and influencing environmental settings, the greater the chances we have of understanding, and potentially mitigating the effects of climate change in these areas.
What are your future career plans?
I hope to be able to continue working within this area of research after the completion of my PhD with a focus on implementing these novel devices in a range of environmental settings to facilitate the collection of new datasets and, in turn, new knowledge.