As an important type of linear cultural heritage and a waterfront landscape that integrates both artificial and natural elements, heritage canals provide the public with a multidimensional perceptual experience encompassing aesthetics, culture, and nature. There remains a lack of refined, micro-level studies on heritage canal landscapes from a multidimensional perspective of visual preference. This study focuses on a typical segment of the Grand Canal in China, specifically the ancient canal section in Yangzhou. We employed SegFormer image semantic segmentation techniques to interpret features from 150 panoramic images, quantitatively identifying the waterfront environmental characteristics of the heritage canal. Four perceptual dimensions were constructed: aesthetic preference, cultural preference, natural preference, and hydrophilic preference. Through a questionnaire survey and various statistical analyses, we revealed the relationships between visual preferences for the waterfront landscape of heritage canals and environmental characteristics. The main findings of the study include the following: (1) Aesthetic preference is positively correlated with cultural, natural, and hydrophilic preferences, while natural preference shows a negative correlation with cultural and hydrophilic preferences. (2) Aesthetic preference is influenced by a combination of blue-green natural elements and artificial factors. Natural preference is primarily affected by increased vegetation visibility, cultural preference is associated with a higher proportion of cultural facilities and high-quality pavements, and hydrophilic preference is linked to larger water surface areas, fewer barriers, and better water quality. (3) There are spatial differences in canal waterfront landscape preferences across different urban areas, with the old city exhibiting higher aesthetic, cultural, and hydrophilic preferences than the new city and suburban areas. Finally, this study proposes strategies for optimising and enhancing the quality of waterfront landscapes of heritage canals, aiming to provide sustainable practical guidance for the future planning and management of these heritage sites.

Historic districts face persistent challenges balancing heritage preservation and urban vitality due to fragmented governance and static conservation. This study develops a multi-source data-driven evaluation system coupling spatial quality and urban vitality, focusing on China’s Republican-era historic districts with Nanjing’s Yihe Road as a case study. Integrating field surveys and big data (street view imagery, POI data, heatmaps), we quantitatively assess environmental quality and vitality. Key findings reveal a distinct spatial pattern: “high-quality concentration internally” and “high-vitality concentration externally,” where core areas exhibit functional homogenization and low vitality, while peripheries show high pedestrian activity but lack spatial coherence. Clustering analysis categorizes streets into four types based on quality and vitality levels, highlighting contradictions between static conservation and adaptive reuse. The study deepens understanding of spatial differentiation mechanisms and reveals universal patterns for sustainable development strategies. A multi-tiered governance strategy is proposed: urban-level flexible governance harmonizes cross-departmental policies via adaptive planning, district-level differentiated governance activates spatial value through functional reorganization, and street-level fine-grained management prioritizes incremental micro-renewal. The research underscores the critical need to balance heritage preservation with contemporary functional demands during urban renewal, offering a practical framework to resolve spatial conflicts and reconcile conservation with regeneration.

Renewal projects dealing with public spaces in Chinese historic neighborhoods were mainly dominated by government entities and experts, but their increasing commercialization and standardization did not fully meet the residents’ needs. In this context, resident-driven regeneration practices centered on small-scale gardening are becoming more popular as an alternative. However, few studies focused on the strengths and intentions of these informal gardens and the implications for the renewal of public space in historical communities. A case study was carried out in the Dashilar area, a historical community with numerous informal gardens. Specifically, resident-led community gardens were first sampled and investigated. Second, the components of these gardens were identified and classified with multiple indicators. Third, agglomerative hierarchical clustering was applied to distinguish the different types and the resident needs behind them, and two kinds of renewal projects were compared. The results show that the spontaneous actions and participation of residents, drawing on local knowledge, are critical to the popularity of informal community gardens among local residents, which is also supplementary to the current organizational mechanisms of public space renewal in historical communities. Our research is expected to enrich the research contents of urban green spaces and provide theoretical support for the sustainable development and renewal of historic neighborhoods.

The arylaluminum reagents are good nucleophiles for organic reactions because of their high reactivity, high chemoselective, low toxicity, and ease of preparation. Therefore, arylaluminum reagents are widely applied in many of organic reactions. This review summarizes the recent advance of the arylaluminum reagents applied in cross-coupling reactions, involving various reaction systems and properties of reaction.

Amid rapid urbanization, cities are becoming increasingly compact, leading to intensified land resource constraints and environmental pressures. As a result, urban parks and green spaces have emerged as critical areas for providing cultural ecosystem services (CESs). However, the spatial distribution of CES supply and demand within urban green spaces remains significantly unbalanced, necessitating precise identification and quantification of CES supply–demand patterns to enhance ecosystem service efficiency. This study uses Nanjing, China, as a case study to develop an indicator framework for urban green space CES supply and demand, leveraging multi-source data. By employing spatial autocorrelation analysis (Bivariate Moran’s I) and a coupling coordination model, this research systematically assesses the spatial patterns of CESs in urban parks and green spaces. The results indicate that the overall CES supply–demand coordination in Nanjing exhibits a “high in the city center, low at the edges, and mismatched in the suburbs” pattern. Specifically, while 9.71% of the areas demonstrate well-matched CES supply and demand, 4.14% of the areas experience insufficient CES demand, and 3.66% face CES supply shortages, primarily in the urban outskirts, leading to a mismatch in green space distribution. This study further reveals the spatial heterogeneity of CES supply–demand matching across different urban districts. Based on these findings, this research proposes optimization strategies to improve CES allocation, providing a scientific basis for urban green space ecosystem service management and promoting the sustainable development of cities.

Cultural ecosystem service (CES) assessment is essential for comprehensively understanding and evaluating ecosystem services. Optimizing the spatial zoning of CESs can provide more targeted information for ecosystem management. By identifying the typical landscape characteristics of different CESs, rural landscape value can be more effectively recognized. This study constructed a set of rural landscape characteristics indicators, identified the typical characteristics of different CESs based on public preferences, mapped their spatial distributions using the Maxent model, and applied K-means clustering analysis to optimize the spatial zoning in rural Huzhou. The results show that the four CESs categories are associated with different rural landscape characteristics. The spatial distributions of the CESs showed substantial overlap and were mainly concentrated in southern Anji County, around the Moganshan Scenic Area, and along the shoreline of Lake Taihu. Five types of rural landscapes were identified based on spatial distribution of the CESs. This study provides a reference for identifying the landscape value of CESs in rural areas and supports the incorporation of CES assessment into rural landscape management decision-making.