index.qmd

# Overview {.unnumbered}

This project develops a modelling system which is able to quantify several competing aspects of land use in a given urban environment, both as it currently exists (the 'baseline'), and also under specific scenarios which change the distribution of such land use.

It comprises a sequence of models, designed to predict the impact of land use changes following large-scale planning decisions on a subset of indicators reflecting the quality of life.
At the same time, it also aims to use neural networks to determine the optimal land use composition given target indicator levels.

The project is a partnership between the [Geospatial Commission](https://geospatialcommission.blog.gov.uk/about-us/) and [The Alan Turing Institute](https://turing.ac.uk), working with [Newcastle City Council](https://www.newcastle.gov.uk/) to develop a modelling system leveraging data science and AI to support decision-making in land use policy.
In particular, the project provides tools to aid decision-makers in strategic planning by:

- evaluating the impacts of large-scale land use changes on policy priorities (house prices, air quality, job accessibility, and greenspace accessibility); and 
- using machine learning and AI to suggest interventions which can achieve desired policy outcomes.