Demonstrating the Potential of Crowdsourcing Science
To illustrate the USGS and FEMA working together in the 2016 Louisiana flood response, the agency has released an interactive Story Map.
In August of 2016, Louisiana, as well as some nearby states, was hit with a historic rainfall event. As a result, approximately 22 of the state’s southern parishes along the Mississippi River system were blanketed with more than seven trillion gallons of rain in a short period of time. This was three times as much rain as the historic Hurricane Katrina flooding. A state of emergency was declared and Federal aid was directed to the affected areas.
Many homeowners in the hardest hit areas did not have home insurance, and as part of their disaster relief effort, the Federal Emergency Management Agency (FEMA) used parcel and structure data to determine where the flooded residences were and how much financial assistance could be provided to homeowners.
However, in six of the 22 disaster-declared parishes, no data existed. To get topographic data, FEMA turned to the USGS and asked for help providing any relevant data.
Relying on the previous successes of crowdsourced data with The National Map Corps program, the USGS invited experienced TNM Corps “editors” to use pre-flood imagery to identify all buildings in the six parishes, distinguishing between and residences and other building types. These experienced volunteer cartographers went quickly to work using available data and editing platforms.
In less than one month very dedicated work, more than 67,000 structure points were collected and identified. Not only was this data used to help FEMA, but it can be turned into a database that can be available to the parish government for their own uses and can serve as a framework for future disaster assistance.
This collaboration illustrates the quick response that the USGS was able to provide in an emergency. It also demonstrates the effectiveness and efficiency of crowdsourced volunteer data collection programs, like TNM Corps, in a time-sensitive task.
To graphically illustrate this complex experiment, the USGS has released a Story Map of the project’s background and success.
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