Our revolutionary science combines streaming remote sensing, machine learning, and community intelligence to dynamically map floods around the world within seconds and predict the communities most at risk to the hazard. The online platform – the Flood Risk Dashboard - enables governments and vulnerable communities to allocate risk reduction funds, operationalize microinsurance, predict disease outbreak, design social and infrastructural programs, and respond to emergencies.
Traditional flood models used for water resources management are slow, expensive, ignore social factors, do not engage communities, and quickly go out of date. Leveraging public and global satilite imagery, The Flood Risk Dashboard could put a holistic flood risk map in everyone’s browser: our data-driven process costs only 1/10th as much as a traditional model and including marginalized communities in decision-making.
Each year 250 million are affected by flooding. The number of people and GDP impacted by flooding is expected to double in the next 13 years due to climate change and population migration. Yet, until today, leading edge flood mapping and vulnerability science was too expensive to be deployed for most communities at the scale and speed of floods. As a result, many of the millions of people living in a floodplain are missing from any public or privately held flood risk map and are under protected.
Our algorithm that harnesses big data, from satellites circling the earth everyday, social media and community crowdsourcing to detect local social and physical vulnerability to flooding in any browser anywhere in the world in seconds. We sell software based a living vulnerability assessment, that updates every time a river changes course, a satellites take a picture and people tweet about floods. We are already providing these services in India and Senegal through on-going contracts with the World Bank and the French Development Bank. The living vulnerability assessment costs 1/10 of the price of traditional flood model’s.
We are currently implementing our flood mapping models and our socio-physicla risk science and algorithm globally to create the largest database of historic floods and in a few highly vulnerability locations (Argentina, Senegal, Uttarakahand (India)) for indepth vulnerability assessments (via the World Bank and the French development agency). When we release the global historic flood database for free in the Fall of 2017 with support from Google Earth Engine and the Dartmonth Flood Observatory, the site will help fill critical data gaps in disaster. The customized vulnerability assessments, implemented through the Flood Risk Dashboard sofware, enables governments and communities to optimize water infrastructure projects like dams and urban drainage systems, implement microinsurance programs, predict disease outbreaks, plan for future climate scenarios, and respond to emergencies. In the Fall of 2017, we plan to begin local fieldwork in Argentina, India and Senegal to engage local communities with our science, assist local water resources managers, and train local leaders.
How does your innovation work?
By leveraging global satellite imagery, social media feeds, machine learning, and the crowd, Cloud To Street makes critical risk information cheap, streamable, inclusive of marginalized communities, and available to the most vulnerable. Our propriety algorithm dynamically identifies the floodplain for any community around the world within seconds and uses predictive analytics to determine who is likely to be impacted by the disaster. Built on our science, our online platform – the Flood Risk Dashboard – will enable governments and communities to optimize water infrastructure projects like dams and urban drainage systems, implement microinsurance programs, predict disease outbreaks, plan for future climate scenarios, and respond to emergencies.
Furthermore, our approach to disaster analysis embeds participatory science and outreach with local stakeholders into the ‘DNA’ of our science and its application. In the dashboard, people can dynamically improve our local flood model by confirming the location of flooding on the street, as well as reveal socially vulnerable communities in their areas. Combining satellite imagery and community input, our dashboards are never out of date – the maps update every time a satellite takes a picture, someone confirms a flood, or a weather prediction changes. Our team and our local in coutry partners will also work with the most vulnerable communities to continually refine the science and support their governments to make better-informed resilience decision.
This people-centered approach transforms technical information into actionable risk awareness and equitable climate resilience efforts.