FloodMapp's data as a service products bring real-time, asset specific flood forecasting and mapping into your GIS system. Helping to operationalise risk mitigation and deliver unrivalled situational awareness for a common operation picture and informed, tactical decision making.
Our live web mapping services integrate directly with your GIS system to deliver unrivalled situational awareness before, during and after a flood.
Flood forecast live mapping data feed API up to 7 days before an event. Plan evacuations. Protect sites and assets.
Real-time flood map live feed API during an event. Maintain situational awareness. Take targeted actions.
“This new technology could help us better prepare for any future flooding event.”
- Hon Karen Andrews MP, Minister for Industry, Science and Technology (2020)
Our Customers & Partnerships.
We work with a diverse network of organisations. One thing they have in common: a desire to improve safety and prevent damage.
FloodMapp partners with the following industries:
Supporting emergency managers with a common operating picture at the local, state and federal level.
Operational flood intel enables analytics, operational road closures and rapid damage assessments to fast track rebuild and recovery.
Helping utilities and asset owners with situational awareness to improve safety and prevent damage to assets.
Be confident in the decisions made with our flood intelligence.
DASH: A new real-time flood model.
DASH (Dynamic Automated Scaleable Hydroinformatics) is purpose built for emergency management and impact-based flood forecasting.
Reading in real-time and forecasted rainfall and river height data from trusted sources, DASH delivers dynamic flood intelligence with live updates that can scale from street level to national views.
Developed by a multidisciplinary team of industry professionals and academics consisting of flood engineers, hydrologists, data scientists and software developers.
DASH combines traditional engineering approaches (hydrology and hydraulics) with cutting edge science and technology (machine learning and automation).
Our models are highly accurate and validated using damage assessment data and crowdsourced flood observations.