Research Article
Spatial Differentiation and Elements Influencing Urban Resilience in the Middle Reaches of the Yangtze River under the COVID-19 Pandemic
Table 7
Results of the global autocorrelation analysis of the in-city travel intensity.
| Variable | Moran’s I | z-score | P | Description |
| Week 1 (2.24–3.1) | 0.569 | 5.24 | ≤0.001 | Clustering pattern | Week 2 (3.2–3.8) | 0.615 | 5.66 | ≤0.001 | Clustering pattern | Week 3 (3.9–3.15) | 0.486 | 4.66 | ≤0.001 | Clustering pattern | Week 4 (3.16–3.22) | −0.146 | −1.12 | 0.262 | Not significant | Week 5 (3.23–3.29) | −0.239 | −2.43 | 0.015 | Discretization pattern | Week 6 (3.30–4.5) | −0.148 | −1.27 | 0.205 | Not significant | Week 7 (4.6–4.12) | −0.064 | −0.32 | 0.746 | Not significant | Week 8 (4.13–4.19) | 0.062 | 1.23 | 0.218 | Not significant | Week 9 (4.20–4.26) | 0.144 | 2.16 | 0.031 | Clustering pattern |
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Correlation is significant at 0.01 level. Correlation is significant at 0.05 level. |