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 helps foster environmentally-friendly patterns of travel, sustainable material management, and increased clean energy use following disasters.
As communities strive to establish new norms following disasters,
opportunities exist to transition toward net positive environmental and societal outcomes,
including increased short-distance local travel and strengthened local supply chains for agriculture and manufacturing.
By tracking changes in local industry input-output, jobs and energy production, model.earth Coding Projects seek to identify shifts toward environmentally-friendly industries during recovery from disasters. Using the US EPA's Environmentally-Extended Input-Output (USEEIO) model, we analyze 24 environmental and health indicators across 380+ industry sectors tracked by the US Bureau of Economic Analysis (BEA).
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. Prior to clean-up, 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
|
NOAA |
Track the Tropics
Strom Tracker |
Mobility Impact |
Storm Stats |
City Boundaries |
Data Processing |
Impact Charts |
Refinements