Strom Tracker | Mobility Impact | Storm Stats | City Boundaries | Data Processing | Impact Charts | Refinements

Impact of Extreme Storms on Mobility and Recovery 2013-2018

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Download Aggregated Data

City Norm and Impact Summary - View online
City Norm and Impact - One Row Per Storm
City Norm and Impact Displacement
Radius of Gyration Compared
Radius of Gyration (1 day segments, 2+ locations)
Radius of Gyration (1 day segments, 3+ locations)
Radius of Gyration (1 day segments, 5+ locations)
Radius of Gyration (3 day segments)
Perturbation (Discrete 6 Steps)
33 Day Spans / Impact and Norm Spans (Private)

Storm Repos (private)

Haiyan (2013-11) - 2 cities
Rammasun (2014-07) - 2 cities
Kalmaegi (2014-09)
Phanfone (2014-10)
Meranti (2016-09)
Matthew (2016-10)
Harvey (2017-08)
Irma (2017-09)
Maria (2017-09)
Lan (2017-10) - 2 cities
Florence (2018-09)
Mangkhut (2018-09)
Michael (2018-10)

Environmental Impacts

Disaster recovery research defines "mobility resiliency" as a measurement of how fast travel patterns return to "normal" following a disaster. Given that "normal" behavior can create unsafe conditions for individuals and negative impacts on the environment, incorporating environmental and health indicators into the study of mobility resiliency could help foster environmentally-friendly patterns of travel, sustainable material management, and increased clean energy use following disasters.

As communities strive to retain the benefits of new norms that emerge following disasters, opportunities exist to transition toward net positive environmental and societal outcomes, including increased local travel and the growth of local supply chains for agriculture and manufacturing. By tracking changes in local industry input-output, jobs and energy production, this study will seek to identify shifts toward environmentally-friendly industries in communities that are recovering from disasters. Using the US EPA's Environmentally-Extended Input-Output (USEEIO) model, this study will combine 24 environmental and health indicators with 380+ industry sectors tracked by the US Bureau of Economic Analysis (BEA). - Loren Heyns, Georgia Tech

Economic and Societal Impacts

From 2013 to 2018, thirty-five storms exceeded a billion dollars in damage and accounted for 80% of direct storm fatalities, causing 14,495 deaths out of 18,111 for all storms.

Google Sheets
Billion Dollar Storms (2013-2018)  |  All Storms (2013-2018)

From these thirty-five storms, storm mobility stats were generated to identify cities with enough geotagged tweets to track changes in mobility during storms. City boundaries were established using city center lat/lons provided by Google, and data was pre-processed using Python and PostgreSql to display Impact Charts using Seaborn and D3.js. The refinements page includes areas for further investigation.

Updated June 26, 2019
Set human movement maximum speed to 150 kmph. Removed known-bots using a list of 24,578 bots combined from 4 studies. Our 16 storm impacts contained 34 known-bots, which posted 8,601 geotagged tweets.

The spreadsheet data above was assembled from 36 Wikipedia pages (6 years, 6 ocean regions) on September 22, 2018. If you'd like to update the data, copy one of the Google Sheets above and add additions from Wikipedia, then write [email protected] to activate. If you have a small change, send an email once you've updated in Wikipedia.

2018 Atlantic hurricane season
2018 Pacific typhoon season
2018 Pacific hurricane season
2018 North Indian Ocean cyclone season
2018-19 Australian region cyclone season
2018-19 South Pacific cyclone season


NCDC Billion-Dollar Weather  |  NOAA  |  Track the Tropics