With the fast pace of global urbanization, anthropogenic disturbances not only lead to frequent disasters, but also cause direct and indirect ecological and economic losses. To reduce the adverse effects of anthropogenic disturbances as part of sustainable ecosystem management, assessments of habitat quality and ecological risk are necessary. The objectives of this study are to analyze environmental conditions of the Beijing-Hangzhou Grand Canal (Suzhou section) for evaluating habitat quality and habitat degradation, and to conduct ecological-risk early warning assessment in this section. The Grand Canal is the longest and first canal in the world to be artificially excavated from natural rivers and lakes. By evaluating habitat quality using the InVEST suite of open-source software models for mapping and valuing the ecosystem, it was found that the natural lands with high habitat quality such as wetlands, forests and lakes along the Suzhou section of the Grand Canal have gradually decreased, while construction lands such as roads and buildings have gradually increased; there is a clear trend of decreasing areas with high habitat quality and increasing areas with low habitat quality, which is likely the result of urbanization. It was also found that the region has a high habitat degradation index, meaning that areas located at the junction of different land types are vulnerable to the surrounding environment due to narrow buffer zones that allow areas with high habitat quality to be easily affected by areas with low habitat quality. In terms of ecological risks, it was found that the natural land area with high habitat quality in the downstream locations was declining, thereby increasing the risks of pollution and flooding events while reducing the ecosystem’s resilience. The valuation model used in this study can be used as an effective decision-support tool to prioritize important ecological areas for conservation in the Grand Canal, and can also be adapted for use in the ecosystem management of other regions.

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.

Balancing urban nighttime development with biodiversity conservation requires a clear understanding of how artificial light at night (ALAN) affects wildlife over time. However, long-term, fine-scale quantitative assessments remain scarce. Here, we analyzed bird diversity and ALAN in Shanghai from 2000 to 2024 at a 1 km resolution by integrating bird observation records with satellite-derived nighttime light data. We quantified the interaction between bird diversity and ALAN using a coupling coordination degree model (CCDM) and identified key drivers with GeoDetector. Our results show that bird diversity increased in 16% of the study area, though spatially fragmented, while ALAN intensified and expanded outward from the urban core, affecting 4.6% of the area. Areas with moderate or higher coordination (CCD > 0.5) nearly doubled, primarily in urban–suburban transition zones. Urban land use, road density, and vegetation cover (NDVI) were the dominant drivers, with NDVI-related interactions significantly enhancing explanatory power. These findings provide the first long-term, spatially explicit assessment of ALAN–bird diversity interactions in Shanghai, offering quantitative guidance for zoning-based lighting management, green space planning, and biodiversity-friendly urban development.

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.