The Global Social Sensing Project is developing new data sources and methods for curating data at scale related to the societal impact and social disruption of natural hazard events. This data is critically important for use in the Earth Sciences, natural hazards research, and in real-time response. As the impact of natural hazard events grow, the ability to pair metrics of social response, and societal disruption, and incident management variables at scale is critical for shaping our understanding of the relationship between societal variables and the physical drivers of natural hazards. Additionally, the ability to mine relevant data in real-time has the potential to save lives and support community response.
Current Projects within the Global Sensing Project include:
The ICS-209-PLUS Dataset a research grade geospatial dataset based on the historical record for the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (see abstract below)
Real-time collection of Incident Status Summary Reports
Using machine learning to mine social media content related to large fires
Mined from the public archive (1999-2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information on incident management costs, personnel, hazard characteristics, values at risk, fatalities, and structural damage. Most (98.5%) of the reports are fire-related, followed in decreasing order by other, hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use due to multiple record formats, inconsistent free-form fields, and no bridge between individual reports and high-level incident analysis. Here, we describe this improved dataset and the open, reproducible methods used, including merging records across three versions of the system, cleaning and aligning with the current system, smoothing values across reports, and supporting incident-level analysis. This integrated record offers the opportunity to explore the daily progression of the most costly, damaging, and deadly events in the U.S., particularly for wildfires.
Lise Ann St. Denis
Lise is a research scientist at Earth Lab responsible for the Global Social Sensing Project, a research initiative to develop datasets Earth scale related to the societal impact and societal disruption of natural hazard events for use in Earth Sciences, natural hazards research, and for real-time response applications.