## 4 Results
### Interaction Detection Results  
Using interaction detection within the Geographical Detector, this section further discusses the explanatory power of CCD when two factors interact (Figure 7). Unlike single-factor detection, factor interactions significantly enhanced the influence of each factor on  
Figure 6: Single-factor detection results of CCD. (**a**) Entire area of lake-ring urban agglomerations; (**b**) Five lake-ring urban agglomerations.  
CCD, indicating that a single-factor approach is insufficient to understand CCD changes comprehensively. For the entirety of China's lake-ring urban agglomerations (Figure 7a), in 2000, HF factor combinations with other factors primarily showed bi-variable enhancement. The most significant interaction effects were observed in LUI\(\cap\)GDP (q = 0.55) and LUI\(\cap\)NL (q = 0.56), indicating that urban expansion and economic development jointly drove the early evolution of human-environment coordination. Although EQ factor combinations exhibited lower contributions (q < 0.4), they demonstrated nonlinear enhancement. In 2010, the interaction patterns of driving factors further intensified. The interaction contributions of LUI\(\cap\)GDP (q = 0.56), LUI\(\cap\)NL (q = 0.58), and POP\(\cap\)GDP (q = 0.47) increased steadily, emphasizing the ongoing dominant role of population and economic activities in CCD changes. While EQ factor combinations maintained nonlinear enhancement, the overall contribution increase was limited. By 2020, the interaction effects grew stronger. The interaction contributions of LUI\(\cap\)GDP, NL\(\cap\)NDVI, and NL\(\cap\)LUI exceeded 0.58, indicating that the coordination mechanism between human activities and the environment became more complex under the dual pressure of economic growth and land use. The interaction between EQ factors, such as NDVI\(\cap\)NDBSI, and WET\(\cap\)LST, also increased. Overall, the dominance of socio-economic factor interactions has continued to rise, while the cumulative effects of ecological factors have gradually become more apparent.  
Figure 7: Factor interaction detection of CCD. (**a**) Entire area of lake-ring urban agglomerations; (**b**) Five lake-ring urban agglomerations.  
The interaction detection results for factor combinations in the five lake-ring urban agglomerations (Figure 7b) indicated that the ranking of interaction factor contributions to CCD followed the order THU > DTU > PYU > CHU > HZU. From 2000 to 2020, the interaction intensity in DTU, PYU, and CHU increased, while HZU and THU declined in 2010 followed by a rebound. For each urban agglomeration, (1) in DTU, the dominant combinations expanded from LUI-related factors to include EQ dimension factors such as NDVI and LST, highlighting the multidimensional evolution of the human-environment coordination mechanism. (2) In PYU, the interaction intensity was relatively weak in 2000. Starting in 2010, the interaction between NL, GDP, and other factors gradually strengthened and further intensified by 2020. It reflects the driving role of economic activities in optimizing the human-environment system. (3) In CHU, the factor interaction intensity before 2010 was mainly dominated by LUI-related combinations. By 2020, the dominant interactions shifted to NL-related combinations, indicating that urban land expansion and economic development led to CCD evolution. (4) In HZU, the overall interaction strength was relatively weak, with HF dimension factors dominating the combinations. The overall q-value increase for EQ dimension factor combinations such as WET\(\cap\)NDVI and WET\(\cap\)NDBSI was limited, indicating that the ecological regulation effect had not yet fully manifested. (5) In THU, the interaction contribution ranked the highest, with NL and GDP-related factor combinations consistently dominating. However, over time, the interaction intensity slightly declined. This reflects that, against stabilized human-environment relationships, the marginal driving effect in THU has weakened, and the system's response elasticity has slowed.