Amidst the rapid global urbanization and economic integration, coastal cities have undergone significant changes in urban spatial patterns. These changes have further worsened the complex urban thermal environment, making it crucial to study the interaction between human-driven development and natural climate systems. To address the insufficient quantification of marine elements in the urban planning of subtropical coastal zones, this study takes Xiamen, a typical deep-water port city, as an example to construct a spatial analysis framework integrating marine boundary layer parameters. This research employs interpolation simulation, atmospheric correction, and other techniques to simulate the inversion of land use and Landsat 8 data, deriving urban morphological elements and Land Surface Temperature (LST) data. These data were then assigned to 500 m grids for analysis. A bivariate spatial auto-correlation model was applied to examine the relationship between urban carbon emission and LST. The study area was categorized based on the influence of marine factors, and the spatial relationships between urban morphological elements and LST were analyzed using a multiscale geographically weighted regression model. Three Xiamen-specific discoveries emerged: (1) the marine exerts a significant thermal mitigation effect on the city, with an average influence range of 7.94 km; (2) the relationship between urban morphology and the thermal environment exhibits notable spatial heterogeneity across different regions; and (3) to mitigate urban thermal environments, connected green corridors should be established in the southern coastal areas of outer districts in regions significantly influenced by the ocean. In areas with less marine influence, spatial complexity should be introduced by disrupting relatively intact blue–green spaces, while regions unaffected by the ocean should focus on increasing green spaces and reducing impervious surfaces and water bodies. These findings directly inform Xiamen’s 2035 Master Plan for combating heat island effects in coastal special economic zones, providing transferable metrics for similar maritime cities.

The rapid increase in global human activities and urban surface modifications has exacerbated the urban heat island effect, prompting growing scholarly efforts to adopt various measures for mitigating heat islands worldwide. This paper reviews existing literature on rooftop mitigation of UHI, summarizes specific existing rooftop mitigation measures, and examines the comparative effectiveness of various rooftop mitigation strategies in reducing urban heat islands. Findings indicate that cool roofs are the most effective rooftop measure for mitigating UHI, followed by green roofs and photovoltaic roofs. Simultaneously, the cooling effectiveness of rooftop mitigation strategies is influenced by their inherent characteristics (reflectivity, coverage, orientation, etc.), geographical and climatic features (latitude, humidity levels, temperature extremes, diurnal temperature variation, etc.), and urban morphology (building density, height, shape index, etc.). The research status summarized herein provides valuable insights for policy formulation and guides future studies, thereby promoting more innovative designs for sustainable urban roofs to mitigate UHI.

Green Infrastructure (GI) has garnered increasing attention from various regions due to its potential to mitigate urban heat island (UHI), which has been exacerbated by global climate change. This study focuses on the central area of Fuzhou city, one of the “furnace” cities, and aims to explore the correlation between the GI pattern and land surface temperature (LST) in the spring and autumn seasons. The research adopts a multiscale approach, starting from the urban scale and using urban geographic spatial characteristics, multispectral remote sensing data, and morphological spatial pattern analysis (MSPA). Significant MSPA elements were tested and combined with LST to conduct a geographic weighted regression (GWR) experiment. The findings reveal that the UHI in the central area of Fuzhou city has a spatial characteristic of “high temperature in the middle and low temperature around,” which is coupled with a “central scattered and peripheral concentrated” distribution of GI. This suggests that remote sensing data can effectively be utilised for UHI inversion. Additionally, the study finds that the complexity of GI, whether from the perspective of the overall GI pattern or the classification study based on the proportion of the core area, has an impact on the alleviation of UHI in both seasons. In conclusion, this study underscores the importance of a reasonable layout of urban green infrastructure for mitigating UHI.

Urban landscape patterns significantly impact land surface temperature (LST) and the urban heat island (UHI) effect. This study employs the boosted regression tree (BRT) model and variance partitioning analysis to examine the contributions and relationships of two-dimensional and three-dimensional building and vegetation patterns to LST, and their marginal effects at different heights. The results show that the dominant indicators affecting LST differ between buildings and vegetation, with three-dimensional building features being slightly more important than two-dimensional features (percentage of landscape of buildings) and two-dimensional vegetation features (three-dimensional green index) having a greater impact than three-dimensional features. When both buildings and vegetation are considered, building patterns still have significant explanatory power. Building height differences influence each indicator’s contribution and marginal effects on LST, with lower-height areas seeing a joint dominance of buildings and vegetation on LST changes, and higher-height areas showing greater impact from vegetation indicators. Increasing the percentage of landscape of vegetation (PLAND_V) provides the best cooling effect in lower-building-height areas, but in higher-building-height areas, the cooling effect weakens, requiring additional vegetation indicators to assist in cooling.

Optimizing urban patterns is increasingly recognized as an effective technological strategy to mitigate the urban heat island (UHI) effect. Taking Xiamen City as a case study, this research extracts and quantifies city spatial characteristics from multiple data sources. Key factors influencing the urban thermal environment were integrated into three primary urban pattern elements: Mountain, City, and Sea. The spatial autocorrelation and heterogeneous impacts of these urban pattern elements on the thermal environment were analyzed using Moran’s I and Geographically Weighted Regression (GWR) modeling, followed by impact-based zoning using K-means clustering algorithms. The results revealed a significant positive correlation between Mountain and City elements and the thermal environment, whereas Sea elements exhibited a notable cooling effect. Furthermore, each factor demonstrated significant spatial heterogeneity. Based on local GWR regression coefficients and spatial variations in factor intensity and directionality, Xiamen was partitioned into four distinct regulatory zones: City-dominated zones, Sea-dominated zones, Mountain–Sea co-dominated zones, and Comprehensive transitional zones influenced by Mountain–City–Sea interactions. Customized, spatially targeted regulatory strategies were subsequently proposed for each zone. This study provides an innovative methodological framework for targeted, region-specific policy interventions to alleviate urban thermal stress under climate change, thereby contributing to the optimization of future urban planning and promoting sustainable and adaptive development.

Amid rapid global urbanization, folk cultural spaces are facing a pronounced “resilience crisis.” Existing studies primarily emphasize material preservation while lacking a holistic assessment of cultural spaces. Using Xiamen Island as a case study, this research integrates GIS-based spatial analysis, questionnaire surveys, and statistical modeling to develop a resilience assessment framework for folk cultural spaces, encompassing four key dimensions: connectivity, modularity, diversity, and adaptability. The study systematically identifies spatial differentiation, formation mechanisms, and typological patterns of these spaces. The main findings are as follows: First, the resilience of folk cultural spaces on Xiamen Island exhibits a spatial pattern characterized by “dual-core leadership, corridor transition, and marginal vulnerability.” High-resilience areas are mainly concentrated in Siming Old Town and the Wuyuanwan district, representing two typical development trajectories—“organic evolution” and “planned intervention.” Second, the influencing mechanisms of each resilience dimension show pronounced spatial heterogeneity, reflecting the coupled effects of structural characteristics, social processes, and governance logics across different urban contexts. Third, three resilience zones are identified through K-means clustering, providing a typological basis for developing differentiated strategies for protection and renewal. This study provides theoretical insights and methodological references for the “living” preservation and adaptive governance of folk cultural spaces.