No abstract

As a type of green infrastructure, greenways are beneficial for walking and cycling and promote urban health and well-being. Taking the Qingshan Lake Greenway Phase One (QLG-I) Trail in the Lin’an District of Hangzhou city as an example and based on the accessibility of points of interest (POI) near the QLG-I Trail, a questionnaire investigation, and an importance performance analysis (IPA), in this paper, we construct a methodological framework to evaluate the health-promotion capabilities of the QLG-I Trail, including three aspects: promoting the coverage of healthy travel, user attribute analysis, and user perceptions of the greenway for health promotion. The results show that the healthy travel range of the QLG-I Trail is small and that the users are mainly residents of nearby communities. Additionally, the main factors affecting users’ health-promoting behaviour are safety, cleanliness, and infrastructure services. Although the overall satisfaction with service quality was good (3.93), we found that the trail facilities did not meet the needs of the users. This study confirms that the QLG-I Trail provides community residents with a place for sports activities and supports health-promoting behaviour. Greenway facilities and the natural environment enhance this utility; however, promoting the coverage of healthy travel is limited by accessibility. Finally, we propose a traffic-organization optimization and improvement plan for the QLG-I Trail. The research results may help promote healthy activities on this type of greenway.

To balance ecological protection and urban development, a land use simulation model that couples an ecological network (EN) and multiple scenarios was developed based on the PLUS model. The simulation of land use in the Qiantang River Basin in 2030 successfully demonstrates the usefulness of the EN-PLUS model. In this model, conventional ecological constraints (nature reserves and water areas) and three different EN levels were taken as restricted conversion areas during the simulation. Then, four ecological constraints were coupled with four simulation scenarios: business as usual (BAU), rapid urban development (RUD), ecological protection (EP), and urban- and ecology-balanced (UEB). Information from the analysis of model simulation results can be used to reduce the potential damage to a range of land cover types. However, this protective effect is not obvious under the RUD scenario due to the impact of significant human disturbance. Furthermore, although EP is the scenario with the least ecological damage at the whole watershed scale, this is not the case for all subbasins. This indicates the existence of a landscape scale effect. Therefore, the best development scenario should be selected by comprehensively weighing the scale effect and the ecological characteristics of each subbasin.

With the continuous promotion of the rural revitalisation strategy, the planning and organisation of individual villages can hardly adapt to the current development needs of rural areas, causing synergistic development among villages to become a critical goal in promoting the sustainable development of rural areas. Reconstructing the development space of traditional village clusters can reduce their development gaps and promote coordinated development. Understanding the connections between traditional village units can support adaptive reconstructions of village spatial network structures and offer scientific and reasonable development planning strategies. Based on geographical and economic data publicly released in 2022, this study takes the traditional villages of the Fuchun River Basin in China as an example and uses village development quality and the shortest traffic time crawled in real time by Python to construct a spatial connection model of traditional villages in the Fuchun River Basin. The study also uses social network analysis to analyse the characteristics of the spatial network structure. The results show that (1) the intensity of spatial connections in these traditional villages is severely polarised and imbalanced. (2) The spatial network structure is in the development stage; few villages act as intermediaries, and the networks have poor connectivity and integrity. (3) The connection density within cohesive subgroups varies considerably. No complete transmission path exists among the subgroups, and the path of collaborative development is imperfect. These findings can optimise and reconstruct the selected spatial network of traditional villages to integrate and upgrade their development. The framework system also holds reference significance for other similar rural traditional villages.

Research on the evolution and driving forces of landscape patterns can provide important support for ecological governance decision-making. However, the heterogeneity of landscape patterns at the microscale (grain size and extent) and the enforceability of the zoning scale at the macroscale deserve more attention. The optimal grain size (30 ×30 m) and the extent (500 m) for landscape pattern research were obtained by analyzing the fluctuation of landscape metrics and semivariogram models in this study. The research area was divided into environmental functional regions (EFRs), which were defined according to the main ecological functions and protection objectives of each region. The analysis results of land use and land cover changes (LUCCs) showed that land use transfer in the past 20 years occurred mainly between woodland and cultivated land at the county scale, but this was not always the case in EFRs. The results of the landscape pattern analysis showed that landscape fragmentation, aggregation, and heterogeneity increased at the county scale during 1999–2020. Moreover, except within agricultural environmental protection areas (AEP) and living environment guaranteed areas (LEG), the degree and the speed of landscape damage decreased by 2020, and the turning point occurred in 2006–2013. The analysis results of geographical detectors showed that the digital elevation mode (DEM) and GDP were the main driving factors in most regions. At the county scale, the average explanatory power of the selected factors increased by 13.27% and 16.16% in 2006–2013 and 2013–2020, respectively. Furthermore, the study area was divided into three categories according to the intensity of human disturbance. The areas with high human disturbance need to focus on increasing land-use intensification and strengthening the development in low-slope hill regions. The areas of moderate human disturbance need to focus on improving the connectivity of ecological patches and optimizing industrial structures. Attention should be given to the monitoring of natural drivers and policy support for ecological governance in low human disturbance areas. The methods and findings in this study can provide a reference for decision-makers to formulate land-use policies, especially for integration into relevant urban planning, such as the spatial planning of national land that is being widely implemented in China.