Climate engagement is key to reducing emissions by changing personal and organisational behaviour. AI methods can be used to reduce the psychological distance to climate impacts in groups who are not actively experiencing the negative effects of climate change in their daily life. Efforts have been made to ‘localise’ the problem, by training networks on disaster imagery and applying that to generate new (‘fictional’) images of places yet to experience the impact of related extreme weather phenomena as a result of climate change.
Our project aims to raise awareness and conceptual understanding of climate change by bringing the future closer. Conceptual interactive website to show precise and personalised impacts of climate change using AI and climate modelling. Bringing together researchers from different fields, the website aims to act as an educational tool that will produce accurate and vivid […]
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A case study from ResearchGate We present a project that aims to generate images that depict accurate, vivid, and personalized outcomes of climate change using Cycle-Consistent Adversarial Networks (CycleGANs). Case Study: Explores the potential of using images from a simulated 3D environment to improve a domain adaptation task carried out by the MUNIT architecture, aiming […]
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