Exploring hyperspectral imaging for non-invasive assessment of green infrastructure status
Entry requirements
Months of entry
Anytime
Course content
In the context of global climate change, there is a growing focus on adaptation and mitigation measures applicable to the built environment. Because of the multi-faceted benefits they can provide, the use of nature-based solutions, including green infrastructure, is an increasingly popular approach. Through both retrofitting and incorporation within new buildings, forms of green infrastructure including green roofs and walls can reduce energy costs and mitigate extreme temperatures through insulation, shading, and evaporative cooling. They can also improve urban air quality by trapping atmospheric pollutants, reduce flooding through interception of rainfall, and increase biodiversity by providing a habitat for pollinators and other insects.
Despite their potential benefits, green roofs and walls require monitoring and maintenance to ensure the incorporated vegetation is not subject to stress caused by factors such as limited availability of water or nutrients, or the presence of pests. There is, therefore, a need for cost-effective methods to assess green infrastructure status that can inform required management. Automated monitoring approaches are particularly attractive, as there is potential to couple them with, for example, irrigation systems, in a ‘smart’ approach that regulates the system without requiring manual human intervention.
Recent work at the University of Salford’s IGNITION Living Lab has highlighted the promising potential of thermographic imaging (i.e. the use of thermal cameras) to identify areas of green roofs and walls under stress, providing valuable information for green infrastructure maintenance (Elkadi et al., 2024). However, such an approach can only detect stress that leads to a change in leaf temperature. It is known that plants may demonstrate a range of other pre-visual signs of stress, including changes in the concentrations of leaf biochemical constituents such as chlorophyll, carotenoids, and anthocyanins. Hyperspectral imaging at the visible and near-infrared wavelengths provides a non-invasive means of assessing these variables (Brown et al., 2024).
Leveraging the School of Science, Engineering & Environment’s recently acquired Cubert ULTRIS X20 Plus hyperspectral camera, this project will explore the potential of hyperspectral imaging for non-invasive assessment of green infrastructure status, with a specific focus on green roofs and walls. The student will benefit from access to the IGNITION Living Lab, which incorporates a range of green infrastructure within the University’s Peel Park campus, where the project will be based.
Fees and funding
This programme is self-funded.
Qualification, course duration and attendance options
- PhD
- part time60 months
- Campus-based learningis available for this qualification
- full time36 months
- Campus-based learningis available for this qualification
Course contact details
- Name
- SEE PGR Support
- PGR-SupportSSEE@salford.ac.uk