The Beijing-Hangzhou Grand Canal carries unique social and cultural significance as a world cultural heritage, but with the acceleration of global urbanization, it has potentially severe environmental risks under continuous anthropogenic disturbances. Therefore, to protect the ecological and cultural values of the Grand Canal, it is necessary to assess the corresponding relationship of water quality to land use and the perception of ecosystem services that focus on cultural ecosystem services (CES). This study aims to analyze the water quality response to land use in the Beijing-Hangzhou Grand Canal, describe the land use types closely related to water quality, and propose corresponding management strategies for enhancing CES. This study investigated the impacts of land use structure and landscape pattern on water quality by calculating the correlation between land use structure and landscape pattern indices and water quality in buffer zones of different distances on both sides of the canal. The results show that green land dominates the land use structure and can effectively reduce water pollution in the canal. On the other hand, urban impervious surfaces showed a significant positive correlation with pollution contributing to low water quality. We accessed the impact of water quality on the perception of CES in the Beijing-Hangzhou Grand Canal and proposed optimization strategies for promoting CES. Both content analysis and thematic analysis were applied to analyze the impact of the water environment quality of the Beijing-Hangzhou Grand Canal on the perception of CES. We found that the perceptions of CES along the Beijing-Hangzhou Grand Canal are associated with the public’s opinions on its cultural heritage services and artistic inspiration services. The perceptions of CES are closely related to the quality of the water environment and riparian greenness, which affect the values of cultural heritage and conservation of the Beijing-Hangzhou Grand Canal.

Land use types other than specialized athletic fields provide a variety of jogging environments, addressing the shortage of urban fitness facilities and promoting urban health as well as sustainability. Currently, there is limited research comparing the differences in jogging support among various land use types, which can assist decision-makers in setting priorities and targeted strategies for urban renewal, especially in urban built-up areas with limited land resources. Initially, spatial information, statistical data, and recommendation reason text were extracted from recommended routes in mobile fitness apps and categorized into six land use types. Subsequently, spatial potential was measured through descriptive statistics, buffer area analysis, spatial autocorrelation analysis, and line density analysis. Environmental preferences were gauged by text analysis using jieba word segmentation and grouped word frequency calculation. Finally, the measurement results of different land uses were compared, including scale differences, spatial differentiation, environmental perception, and environmental elements. The research found that streets, residential areas, campuses, parks, and greenways possess significant potential to support jogging, particularly streets. These types of land use exhibit varying spatial potentials and attractions in environmental preferences. Targeted recommendations have been proposed to support the renewal of urban built-up areas and research in related fields.

As an integral part of rural built heritage, the aesthetic and recreational values of Historical Irrigation Canals (HICs) have increasingly garnered attention in recent years, providing new perspectives for heritage conservation and sustainable rural development. However, there is a scarcity of research conducted from the micro-perspective of public preferences for HICs in rural areas. The existing literature primarily focuses on how the landscape characteristics of natural and urban rivers affect public preferences, with a lack of attention to built heritage characteristics and rural settings, which are uniquely inherent to HICs in rural areas. This study aims to explore public preferences for HICs in rural areas from the perspectives of landscape characteristics and social backgrounds. The Li Canal-Gaoyou Irrigation District, one of the World Heritage Irrigation Structures, was selected as the case study. Selected HIC photos were utilized for measuring landscape characteristics and conducting survey questionnaires. Relationships among HIC landscape characteristics, social backgrounds, and aesthetic and recreational preferences were revealed through one-way ANOVA, Spearman’s correlation, and stepwise regression analyses. Key findings include the following: (1) the public can derive aesthetic and recreational value from HICs; (2) canals with large water bodies, artificial banks, and artificial vegetation are considered more aesthetically pleasing; (3) larger canals, extensive water bodies, and artificial banks are deemed more suitable for recreation; (4) factors such as age, education level, income, rural living experience and knowledge of HICs influence public preferences; (5) costs influence public aesthetic and recreational preferences, with people more willing to pay for roads and hardened banks. Finally, several recommendations for the protection and management of HICs have been summarized, offering guidance for rural managers and planners.

Improving street jogging environments can promote urban health and sustainability, especially within urban built-up areas. Public attention to the environment during jogging has not been sufficiently studied, and the recommended route data from the fitness app offers an opportunity for multiscale spatial exploration. Initially, by analyzing the recommendation reason text, the study identified 22 environmental factors and proposed the Environmental Factor Public Attention Intensity (EFPAI) for quantification, with subsequent comparisons to expert opinions. Further, by analyzing five types of data from the recommended routes, the relationships between EFPAI and jogging frequency, route shape, spatial distribution, and seasonal variations were uncovered. The study revealed: (1) discrepancies between expert opinions and public attention, with experts more likely to overlook factors such as slope, visual quality, width, and acoustic quality; (2) the public tends to notice factors like pedestrians, green spaces, waterfront spaces, landscapes, culture, sports facilities, and accessibility on routes with high jogging frequency; (3) EFPAI for traffic infrastructure, waterfront spaces, landscapes, residential areas, and campuses is associated with route shape; (4) EFPAI of certain environmental factors is influenced by urban geographical spatial factors, and substantial differences exist between different cities. Specific recommendations were provided from three different scales—site scale, street block scale, and urban scale—to guide the resolution of issues in planning and decision-making processes for urban renewal.

The construction of post-industrial landscapes is increasingly regarded as an important pathway for promoting urban sustainability. However, limited attention has been given to the interconnections between post-industrial landscapes and local villagers in rural contexts. From the perspective of environmental justice, the ecological and cultural-tourism goals of post-industrial landscapes may be mismatched with villagers’ place-based needs. This study examines a typical rural post-industrial waterfront area in China to analyze villagers’ environmental justice. Representative project photographs were collected, and villagers’ perceptions were obtained through questionnaires and semi-structured interviews, yielding 98 valid responses (95% response rate). Quantitative measurements of landscape characteristics were combined with pairwise preference evaluations, and the analysis applied the framework of recognition, participatory, and distributive justice. A discrete choice model (DCM) and spatial analysis were then employed to explore the relationships. Quantitative analysis showed that natural vegetation, plazas, industrial heritage, and pedestrian paths had negative effects on villagers’ recognition (β = −0.36 to −0.18), whereas hardscape had a strong positive effect (β = 0.94). Moreover, spatial analysis indicated localized patterns of environmental injustice, highlighting uneven distribution of landscape benefits across the site. Semi-structured interviews revealed villagers’ priorities across landscape design, amenities, local livelihoods, and project implementation, highlighting the importance of safer, more functional, and well-managed spaces. Collectively, these findings underscore the importance of inclusive planning and design strategies that integrate ecological, cultural, and recreational considerations, thereby supporting the sustainable renewal of rural post-industrial waterfronts.

In high-density urban areas where land is at a premium, Informal Running Environments (IRE) provides opportunities for mixed use, which is conducive to improving the current problem of insufficient and uneven distribution of fitness space. Running environments dominated by linear space are often difficult to study through traditional research methods, while the emergence of the crowdsourcing model enables Volunteered Geographic Information (VGI) to provide effective data support. Firstly, text semantic analysis was done based on the recommended route data from mobile fitness APP. The key factors and importance levels that influence people's preference on IRE are identified. Secondly, a supply and demand evaluation for the informal running environment was constructed. Priority areas for renewal in the city were identified. Finally, a strategy toolbox containing visual case patterns was developed to provide decision-makers with directional and easy-to-implement guidance. Key factors such as people, paving, lighting, vehicles, residential areas, transportation facilities, green spaces, waterfront and scenery were found to have a significant impact on running behavior. The research provides a quantitative evaluation and optimization method for urban renewal.