## 4 Discussion
### Identification and Suggestions for Key Regulatory Areas
#### 4.3.2 Identification for Cold/Hot Spots of Ecological Quality Changes and Suggestions  
Table S5 presents the global Moran's I test results for the three study areas, with the \(p\)-value determined through 999 iterations of the Monte Carlo random permutation test. It can be inferred that both high- and low-value areas of EQI exhibit significant spatial clustering features (\(p<0.0001\)) [118]. Subsequently, Local Indicators of Spatial Association (LISA) were employed to describe the heterogeneity of EQI clustering features and offer insights for planning and management in BTH, CYRD, and PRD. It is noteworthy that we reversed the detection focus of LISA to identify hotspots of ecological damage. The High-High (hotspot) areas and Low-Low (cold spot) areas were compared. As depicted in Figure 12, urbanization-induced ecological deterioration predominantly induces clustering in the \"High-High\" areas. Conversely, the \"Low-Low\" pixels have increased in the west of PRD, indicating improved EQI (Figure 12c,f). This underscores the potential for enhancing environmental quality through the establishment of ecological barriers or the implementation of ecological protection measures [40]. Additionally, it was observed that \"Low-Low\" clusters largely correspond to regions with favorable EQI conditions (Figure 3). Two notable patterns, \"Low-High\" and \"High-Low,\" are also evident. The \"Low-High\" clustering pattern is primarily distributed in the southeastern part of BTH, with scattered pixels in hotspot areas facing a higher potential for further degradation (Figure 12d). These regions represent key areas requiring coordinated planning for agricultural production land and protection against urban development encroachment. \"High-Low\" pixels correspond to damaged or potentially damaged forested regions, providing planning suggestions for establishing protected areas (Figure 12d-f). Analyzing the spatial heterogeneity of different regions is crucial for formulating targeted management policies. From the perspective of spatiotemporal changes in ecological quality, attention should be directed towards the expansion direction of cities, particularly in the surrounding areas of the initial urban zone. These areas include the southeastern part of the BTH region, the Yangtze River coast, the environs of Shanghai, and the central part of PRD. Persistent threats to ecological land use, such as arable land encroachment, land reclamation from lakes, and excessive animal husbandry, necessitate the development of specialized management policies for the urban-rural fringe. Additionally, raising  
Figure 11: The spatial distribution of EQI change (\(\Delta\)EQI) in urban agglomerations. (**a–c**) Spatial distribution of EQI change (\(\Delta\)EQI) in BTH, CYRD, and PRD, respectively. awareness among farmers regarding ecological protection can be an effective measure. Furthermore, monitoring the ecological quality of regions exhibiting \"High-Low\" and \"Low-High\" clustering modes in Figure 12 is essential, given their higher potential for ecological changes. Additionally, substantial disparities exist in urbanization intensity and ecological quality changes among different cities. As depicted in Figure 7, commendable efforts in balancing economic development and ecological environment protection have been observed in the Yangtze River Delta region. Valuable lessons can be drawn from cities such as Chizhou, Hefei, and Huizhou, which have experienced high urbanization intensity coupled with improved ecological quality over the past two decades. Conversely, cities like Langfang, Qinhuangdao, and Tangshan, characterized by lower urbanization intensity but more severe ecological quality damage, should promptly implement ecological protection measures. Measures to reduce dependence on heavy industry and promote sustainable new energy sources can effectively enhance air quality.