Table 2 Comparison of resilience, transient loss of resilience and recovery time for multiple types of events occurred in different location
From: Quantifying human mobility resilience to extreme events using geo-located social media data
Disaster Name | Location | Threshold Z Score | Location Filter | Start Time | Recovery Time (hr.) | Max Deviation | Resilience (R) | Transient Loss of Resilience (TLR) | Ratio (TLR/R) |
|---|---|---|---|---|---|---|---|---|---|
Sandy | New York City | \(\alpha_{l}=60\) | Y | 2012-10-26 00:00 | 132 | 0.540 | 106.730 | 19.260 | 0.181 |
\(\alpha_{l}=40\) | N | 2012-10-28 12:00 | 66 | 0.010 | 17.620 | 42.370 | 2.404 | ||
New York State | \(\alpha_{l}=40\) | Y | 2012-10-28 12:00 | 48 | 0.260 | 21.860 | 20.100 | 0.920 | |
\(\alpha_{l}=40\) | N | 2012-10-28 06:00 | 144 | 0.087 | 36.400 | 101.400 | 2.730 | ||
New Jersey State | \(\alpha_{l}=60\) | Y | 2012-10-28 00:00 | 120 | 0.176 | 52.000 | 55.00 | 1.057 | |
\(\alpha_{l}=60\) | N | 2012-10-27 12:00 | 168 | 0.001 | 21.179 | 140.820 | 6.648 | ||
| Â | Â | 2012-11-06 00:00 | 48 | 0.018 | 8.907 | 33.090 | 3.715 | ||
Pennsylvania State | \(\alpha_{l}=60\) | Y | 2012-10-28 00:00 | 120 | 0.180 | 58.930 | 49.060 | 0.833 | |
\(\alpha_{l}=60\) | N | 2012-10-26 06:00 | 144 | 0.003 | 12.600 | 125.390 | 9.949 | ||
| Â | Â | 2012-11-02 06:00 | 72 | 0.015 | 13.970 | 52.026 | 3.720 | ||
Earthquake | Bohol, Philippines | \(\alpha_{u}=90\) | NA | 2013-10-15 00:00 | 54 | 9.330 | 120.470 | 162.310 | 1.340 |
| Â | Â | 2013-10-19 18:00 | 24 | 11.035 | 64.956 | 115.680 | 1.780 | ||
Iquique, Chile | \(\alpha_{u}=90\) | NA | 2014-04-02 18:00 | 48 | 38.167 | 519.058 | 344.890 | 0.664 | |
Napa, USA | \(\alpha_{u}=90\) | NA | 2014-08-23 18:00 | 18 | 6.416 | 27.490 | 37.503 | 1.360 | |
Wild Fire | NSW1, Australia | \(\alpha_{u}=90\) | NA | 2013-10-18 12:00 | 18 | 8.257 | 58.860 | 28.230 | 0.480 |
\(\alpha_{l}=40\) | NA | 2013-10-19 06:00 | 48 | 0.188 | 22.440 | 19.550 | 0.870 | ||
NSW2, Australia | \(\alpha_{l}=40,60\) | NA | NO TLR | ||||||
Winter Storm | Xaver, Norfolk, Britain | \(\alpha_{l}=40\) | NA | 2013-12-02 12:00 | 48 | 0.339 | 25.370 | 16.629 | 0.655 |
Xaver, Hamburg, Germani | \(\alpha_{l}=40\) | NA | 2013-12-04 18:00 | 48 | 0.035 | 24.817 | 17.182 | 0.690 | |
\(\alpha_{u}=90\) | NA | 2013-12-13 12:00 | 36 | 4.306 | 55.704 | 43.480 | 0.780 | ||
Atlanta, USA | \(\alpha_{l}=40\) | NA | 2014-01-28 12:00 | 54 | 0.261 | 20.450 | 27.545 | 1.346 | |
Rain Storm | Phoenix, USA | \(\alpha_{l}=40\) | NA | 2014-09-06 18:00 | 60 | 0.329 | 40.000 | 13.000 | 0.413 |
Detroit, USA | \(\alpha_{l}=40\) | NA | Not Enough Pre-Disaster Data | ||||||
Baltimore, USA | \(\alpha_{l}=40,60\) | NA | NO TLR | ||||||
Typhoon | Wipha, Tokyo, Japan | \(\alpha_{l}=40,60\) | NA | NO TLR | |||||
Halong, Okinawa, Japan | \(\alpha_{l}=40\) | NA | 2014-07-29 06:00 | 96 | 0.616 | 74.000 | 10.000 | 0.135 | |
Kalmaegi, Philippines | \(\alpha_{l}=40\) | NA | 2014-09-08 12:00 | 96 | 0.005 | 42.568 | 42.000 | 0.990 | |
\(\alpha_{l}=40\) | Â | 2014-09-23 12:00 | 54 | 0.003 | 24.188 | 23.811 | 0.980 | ||
Rammasun, Philippines | \(\alpha_{l}=40,60\) | NA | NO TLR | ||||||