The foundation of any initiative to ensure towns and cities are resilient to the impacts of climate change lies in acquiring and analysing information and data on hazards, the assets and individuals that might be exposed to these hazards and the degree to which they are vulnerable to harm. Climate models, satellite remote sensing, surveys and participatory approaches have all been used for this. However, the data and information acquired from these efforts has a degree of uncertainty, lacks granularity and is not as reliable and verifiable as it could be. Therefore, this chapter explores how a new generation of approaches that draw on “big data”, machine learning, artificial intelligence and innovative information and communication technologies can help bridge these gaps. As such, the chapter urges the global community of practice working to enhance the resilience of towns and cities to employ these novel, cost-effective and impactful approaches alongside the existing suite of methods they use to acquire and analyse climate information and data.