Mapping the local heat transition: from large-scale geospatial data to real-world impact
Decarbonising UK’s home heating is one of the greatest challenges of the Net Zero transition, yet it currently relies on individual household decisions supported by government incentives. To help accelerate the local delivery, we are building tool that maps the most suitable low-carbon heating for clusters of properties at a neighbourhood level.
In this talk we will walk through our end-to-end data science pipeline, covering processing of large-scale geospatial data, the nuances of modelling where ground truth data does not yet exist, and how to translated local authorities needs into a functional product. We will present our Python tech stack and will conclude with a showcase of the user interface.
Whether you're interested in geospatial data engineering, machine learning for social good, or how to work within a multidisciplinary team, this talk offers a blueprint for building data products with real-world impact.