## 4 Results
### Spatiotemporal Evolution Patterns of HF and EQ
#### 4.1.2 Spatiotemporal Evolution Characteristics of EQ  
Figure 4a illustrates the numerical development trend of EQ in China's lake-ring urban agglomerations. Overall, the EQ values in the lake-ring urban agglomerations demonstrated a fluctuating trend over the 20 years. The multi-year average proportion of low-value areas remained relatively low (13.27%), showing a trend of initial decline followed by recovery. The buffer zone decreased from 39.08% to 31.84% in the first 10 years and rose to 36.10%. High-value areas maintained the highest multi-year average proportion (51.06%), increasing from 47.00% to 56.88% before falling back to 49.30%. For the five lake-ring urban agglomerations, the following patterns were observed. For each urban agglomeration, (1) the category proportion ranking for DTU and PYU was low-value areas < buffer zone < high-value areas. The two agglomerations exhibited significantly different evolution trends. DTU displayed a trend of continuous deterioration, with the proportion of low-value areas increasing by 139.14%. In contrast, PYU showed an improving trend, with the high-value area rising to the highest level across the region (64.64%) by 2020. (2) CHU and HZU exhibited a trend of initial improvement followed by deterioration,  
Figure 3: Spatiotemporal evolution characteristics of HF. (**a**) Numerical development trend of different HF levels; (**b**) Mean values and spatiotemporal distribution patterns of HF. indicating the high sensitivity of lake-ring urban agglomeration ecosystems to external disturbances. Notably, HZU experienced greater fluctuations than CHU, mainly due to urbanization expansion, changes in lake humidity, and vegetation coverage. (3) As the urban agglomeration with the lowest HQ level, THU showed the highest and lowest multi-year average proportions of low-value and high-value areas, respectively (29.42% and 26.78%). Over time, the buffer zone and high-value areas continuously decreased, while the low-value areas continuously increased, with change rates of \(-20.11\%\), \(-44.81\%\), and 210.01%, respectively. The deterioration of EQ in THU is likely linked to declining vegetation coverage, surface drying, and degradation of the thermal environment. Figure 4b presents the raster-based visualization analysis of the spatiotemporal evolution pattern of China's lake-ring urban agglomerations from 2000 to 2020. Overall, the mean EQ values from west to east were 0.6486, 0.6237, 0.5492, 0.5728, and 0.4799, respectively, forming a distribution pattern opposite to that of HF, with higher values in the west and lower values in the east. For each urban agglomeration, (1) DTU and PYU exhibited a concentric progressive structure. Lake-ring low-value areas occupied the first layer, buffer zones overlapped with croplands to constitute the second layer, and high-value areas composed the third layer in the peripheral forest regions. During the study period, the first layer increasingly converged toward the city center, the second layer displayed an unstable distribution, particularly shifting from the southeast to the northwest in DTU,  
Figure 4: Spatiotemporal evolution characteristics of EQ. (**a**) Numerical development trend of different EQ levels; (**b**) Mean values and spatiotemporal distribution patterns of EQ. and the third layer showed weak spatial fluctuations. (2) CHU and HZU underwent significant spatial pattern changes. In 2000, CHU was dominated by the III-level buffer zone. HZU formed a heterogeneous distribution with III-level in the east and II-level in the west, divided by Hongze Lake. By 2010, the I-level low-value areas around the core cities of Hefei and Huai'an had significantly expanded. Additionally, a large portion of the buffer zone shifted to high-value areas. By 2020, the high-value area partially receded, while the low-value area continued expanding toward the outer suburbs of the core cities. (3) THU exhibited a multi-core low-value aggregation pattern centered around cities such as Shanghai, Suzhou, Wuxi, Changzhou, and Hangzhou.