In the context of waterfront-space design, this study examines the impact of plant enclosures and the ratio of water bodies to green spaces on the microclimate, aiming to enhance the climate environment and mitigate urban heat. Utilizing Fujian Agriculture and Forestry University as a case study, the research selects the summer solstice as a representative weather condition, conducts field measurements and model validation for four types of waterfront vegetation, and creates 80 scenarios with varying plant enclosures and water to green space ratios using ENVI-met 5.0.2software. This comprehensive analysis seeks to identify the optimal water–green space ratio for waterfront areas. Key findings include: (1) The efficacy and applicability of ENVI-met software for microclimate studies are confirmed. (2) Waterfront plants have cooling and humidifying effects on the microclimate environment. The order of cooling and humidifying effects of different plant community structures was as follows: tree–shrub–grass > tree–grass > shrub–grass > grass. (3) The cooling, humidification, ventilation, and human comfort levels are influenced by the specific enclosure conditions and water to green space ratios; a ratio of 1.8:1 is the most effective for cooling and improving human comfort, while ratios of 4:1 and 1:4 are better for humidification and ventilation. These results offer valuable insights for designing waterfront spaces in hot and humid climates.

The coordinated development of park green spaces (PGS)with urban functional areas (UFA) has a direct impact on the operational efficiency of cities and the quality of life of residents. Therefore, an in-depth exploration of the coupling patterns and influencing factors between PGS and UFA is fundamental for efficient collaboration and the creation of high-quality living environments. This study focuses on the street units of Fuzhou’s central urban area, utilizing multi-source data such as land use, points of interest (POI), and OpenStreetMap (OSM) methods, including kernel density analysis, standard deviational ellipse, coupling coordination degree model, and geographical detectors, are employed to systematically analyze the spatial distribution patterns of PGS and UFA, as well as their coupling coordination relationships. The findings reveal that (1) both PGS and various UFA have higher densities in the city center, with a concentric decrease towards the periphery. PGS are primarily concentrated in the city center, exhibiting a monocentric distribution, while UFA display planar, polycentric, or axial distribution patterns. (2) The spatial distribution centers of both PGS and UFA are skewed towards the southwest of the city center, with PGS being relatively evenly distributed and showing minimal deviation from UFA. (3) The dominant type of coupling coordination between PGS and various UFA is “Close to dissonance”, displaying a spatial pattern of “high in the center, low on the east-west and north-south wings”. Socioeconomic factors are the primary driving force influencing the coupling coordination degree, while population and transportation conditions are secondary factors. This research provides a scientific basis for urban planning and assists planners in more precisely coordinating the development of parks, green spaces, and various functional spaces in urban spatial layouts, thereby promoting sustainable urban development.

Although tourists’ multi-attraction visitation behavior in tourism flow networks appears random, it actually follows underlying association rules. These rules may exhibit regional variations due to the influence of administrative barriers. Revealing the attraction association rules connected through tourist behavior can provide theoretical support for regional tourism planning and resource allocation. This study proposes a novel analytical framework to uncover hidden patterns and driving factors in tourists’ seemingly random behaviors across inter- and intra-township scales, with empirical evidence from the Pilot Zone of the Yangtze River Delta Green and Integrated Ecological Development Demonstration Area. Results show that the tourism flow network in the study area exhibits a distinct hierarchical structure. Nodes with high centrality are predominantly high-profile scenic spots that serve dual roles as both “cores” and “hubs” in the network. Most statistically significant association rules were observed at the intra-town level. In contrast, inter-town rules (exclusively among towns within Qingpu District, Shanghai) accounted for only a small proportion, where high-A-level tourist attractions frequently served as key nodes that enhanced cross-regional visitation probability. The determinants of tourist flow association rule intensity exhibit both commonalities and heterogeneities between intra-town and inter-town scales.