Figures & data
Table 1. Landscape metrics used in the study.
Table 2. Result of principal component analysis.
Figure 4. Identifying region of interest through scatterplot (the first metric is PD and the second metric is AI.
![Figure 4. Identifying region of interest through scatterplot (the first metric is PD and the second metric is AI.](/cms/asset/a06a7e83-4638-4bb4-a052-f2748c047beb/tagi_a_1615550_f0004_oc.jpg)
Figure 6. Data fusion panel. The example illustrates the relationship between economic change and urban metrics (CA, AI and Cohesion).
![Figure 6. Data fusion panel. The example illustrates the relationship between economic change and urban metrics (CA, AI and Cohesion).](/cms/asset/cc9c5e3a-05cd-459e-9876-8e84845a22cf/tagi_a_1615550_f0006_oc.jpg)
Figure 7. Data fusion panel (an example of exploring the relationship between population change and landscape metrics).
![Figure 7. Data fusion panel (an example of exploring the relationship between population change and landscape metrics).](/cms/asset/2ae69cfa-87d5-4ca0-ad17-bf381b0976db/tagi_a_1615550_f0007_oc.jpg)
Table 3. Regions of interest based on urban CA metric.