Time And Relative Dimensions in Science

Sand grains get everywhere in our landscapes - beaches, deserts, rivers. They can tell us a lot about past sea level changes, droughts and floods but only if you know how to interrogate them right. The technique of Luminescence dating can show how old sand grains are and help us to understand when past climate and environmental changes took place. This demonstration will show the science behind luminescence dating with real life sand grains revealing their relative ages!

Data is everywhere and can increasingly give us insights into our complex urban systems and cities. Detailed spatial data on the neighbourhood environment and urban hazards paired with secondary data sources can help us understand how people value and interact with their locations. We can leverage this environmental-urban data science framework using pollution (the red), flooding (the blue), and our urban flora (the green) to build environ-equitable and resilient communities going forward – led by best practices and research-driven policies

To simulate floods, we need to understand how flooding occurs in the real-world. An affordable way of doing this is to use computer simulations to create flood hazard maps, which tell us about the chance of flooding at any particular place. Creating these maps requires data on expected rainfall, river flows and terrain, and confidence in the forecasts largely depends on our confidence in the input data. As we collect higher quality data, then our forecasts will continue to improve.