Taking the lower Yellow River basin as the study area, this study aims to construct ecological networks to mitigate the negative impacts of rapid urbanization on the ecosystem. Ecological sources were identified based on morphological spatial pattern analysis (MSPA), habitat quality and landscape connectivity. The ecological resistance surface was constructed and corrected by integrating natural and anthropogenic factors. The spatial range of ecological corridors and some of their key nodes were identified based on circuit theory. The ecological network (EN) was finally optimized using a similarity search and cost connectivity modules. The results show that the optimized ecological network structure is more stable than before. The EN includes 23 ecological sources with a total area of 5464.8 km ² and 30 ecological corridor clusters with a total area of 2205.92 km ² . Through the internal landscape heterogeneity of the corridor, 28 ecological node areas and 75 barrier areas were identified as key protection and restoration areas, with a total area of 78.44 km ² and 372.79 km ² , respectively. Through the construction and optimization of EN, this study identifies key areas for promoting ecological sustainability and provides a useful framework for coordinating regional ecological conservation and economic development.

The spatial distribution and accessibility of urban public service facilities affect socioeconomic factors in the lives of residents, especially housing prices. Given that most previous studies focus on the accessibility of a certain, single type of facility and its impact on housing prices, this research uses improved two-step floating catchment area (2SFCA) methods by considering the differences in the service capacity of different types of public service facilities in real life to evaluate their accessibility to residential communities in Jinan city based on 3117 facilities covering 11 different kinds of facilitates. Then, we assess the spatial distribution of the impact of the accessibility of different public service facilities on housing prices in Jinan city through a local indicator of a spatial association (LISA) cluster diagram generated based on the bivariate local Moran’s index. Our objectives are to assess the accessibility of multiple public service facilities using an improved 2SFCA method and to explore the spatial correlations between the accessibility of public service facilities and housing prices. The results show that the housing prices in Jinan are clustered and that the areas with high housing prices are mainly concentrated in the Lixia District and the center of the downtown area. The accessibility of medical, shopping, educational and bus stop facilities in the Lixia District is better than that in other districts. The accessibility of shopping, medical and tourist attraction facilities has the most significant impact on housing prices, and the number of communities in which the accessibility of these public service facilities and housing prices form a positive correlation cluster accounts for 50.5%, 47.9% and 45.8% of all communities, respectively. On the other hand, educational accessibility and bus stop accessibility have nothing to do with housing prices, and the number of communities in which the accessibility of these public service facilities forms a not-significant cluster with housing prices accounting for 51.1% and 56.5% of the total, respectively. In this study, the combined 2SFCA method is used to improve the method for evaluating the accessibility of a variety of public service facilities, and its applicability is verified by practical application. By analyzing the spatial correlation between accessibility and housing prices, we expand our understanding of accessibility and show that it plays a central role in housing prices, which will help to improve the spatial pattern of urban public places in the future, provide support for decision makers and provide a reference for the government and real estate developers.