Abstract: Abstract: Objective In the contemporary global context, urban areas are increasingly confronted with the dual pressures of global climate change and rapid urbanization. These pressures have led to a significant rise in urban temperatures, thereby amplifying the importance of blue-green spaces in mitigating the urban heat island (UHI) effect. Blue-green spaces, which include natural water bodies, parks, green corridors, and other vegetated areas, play a crucial role in regulating urban microclimates. As cities enter an era of stock development, where the focus shifts from expansion to optimization of existing resources, the strategic configuration of these spaces has become a cornerstone for enhancing urban thermal environments. Understanding the cooling mechanisms of blue-green spaces at various spatial scales is essential for improving urban thermal comfort and guiding the planning and construction of urban blue-green infrastructure. Methods This study focuses on the central urban area of Xi''an, a city that has experienced substantial urban growth over the past decade. By employing a combination of spatial autocorrelation analysis and a multi-scale geographically weighted regression model (MGWR), the research examines the characteristics of blue-green space changes and their impact on land surface temperature (LST) from 2013 to 2023. The findings reveal the spatial heterogeneity of cooling effects and offer tailored optimization strategies for blue-green spaces across diverse urban contexts. The research methodology involved the selection of six representative landscape indices to evaluate the changes in blue-green space patterns in Xi''an''s central urban area. These indices were carefully chosen to capture the nuances of spatial configuration, fragmentation, and connectivity of blue-green spaces. Spatial autocorrelation analysis was utilized to identify spatial clustering and patterns in the data, while the MGWR model allowed for a more granular examination of the relationship between landscape indices and LST levels. This integrated approach not only revealed the factors influencing the cooling effects of blue-green spaces but also highlighted their spatial variability across the urban landscape. Results The results of the study are both revealing and instructive. （1）The blue-green space patterns in Xi''an''s central urban area underwent significant changes over the study period, reflecting the dynamic interplay between urban development and environmental management.（2） The spatial distribution of LST exhibited a distinct "high in the north and low in the south" pattern. The central region, characterized by dense urban fabric, showed minimal fluctuations in LST, whereas low-temperature zones were predominantly concentrated in the southern part of the Baqiao District. This uneven thermal distribution underscores the complexity of urban heat dynamics and the need for targeted interventions.（3） The relationship between landscape indices and LST changes displayed notable spatial heterogeneity. In high-density urban areas, small and complex blue-green patches demonstrated stronger cooling effects, emphasizing the importance of intricate designs in densely built environments where space is limited but the need for effective cooling is paramount. In contrast, suburban areas benefited from avoiding the aggregation of large blue-green patches, which could otherwise hinder effective cooling due to reduced air circulation and increased shading. Near large water bodies, regularly shaped and highly connected blue-green patches were found to be particularly effective in reducing LST, highlighting the synergistic effects of water and vegetation in enhancing cooling performance and suggesting that integrated blue-green networks can maximize thermal benefits.(4)By utilizing holistic indicators of urban blue-green spaces, the study explored their influence on cooling mechanisms. This comprehensive approach provided a foundation for developing strategies to mitigate the urban heat island effect and optimize blue-green space management. The findings suggest that the cooling effects of blue-green spaces are contingent upon their area, shape, and aggregation in different spatial regions. For instance, in high-density urban cores, smaller and more fragmented blue-green patches were more effective, while in suburban and peri-urban areas, larger and more contiguous patches were preferable. Additionally, the spatial configuration of blue-green spaces near water bodies emerged as a critical factor, with regular shapes and high connectivity enhancing cooling performance. Conclusion The study concludes that from 2013 to 2023, the relationship between temperature changes and blue-green space changes in Xi''an''s central urban area was significant and characterized by strong spatial heterogeneity. The cooling effects of blue-green spaces were found to vary based on their spatial attributes and the characteristics of the surrounding urban environment. These findings highlight the necessity for region-specific optimization strategies to maximize the cooling potential of blue-green spaces.By integrating spatial analysis and regression modeling, the study provides a detailed understanding of the cooling mechanisms of blue-green spaces across diverse urban contexts. The results emphasize the importance of tailoring blue-green space designs to local conditions, considering factors such as urban density, proximity to water bodies, and regional climatic characteristics.This approach enhances the effectiveness of blue-green spaces in mitigating the urban heat island effect and contributes to the creation of more sustainable and thermally comfortable urban environments. The study advocates a holistic and adaptive urban planning strategy, where blue-green spaces are strategically designed and managed to address the unique thermal challenges of different urban areas. This research offers valuable guidance for policymakers and urban planners aiming to optimize blue-green infrastructure and improve urban resilience in the face of climate change and urbanization.