Understanding the driving forces behind built-up land expansion is crucial in urban planning and management. Using the Pearl River Delta urban agglomeration as research area, four landscape metrics were used to analyze landscape characteristics of urban expansion from 1990 to 2015. Spatial autocorrelation analysis was used to study the characteristics of built-up land expansion, while geographical detector was employed to identify the driving forces of urban land growth and their interactions. The results show the extent of built-up land has been increasing, the structure has become more complex, the level of fragmentation has been increasing, and the aggregation degree is in decline. The built-up landscape index shows spatial heterogeneity occurring in the core and peripheral towns of cities, as well as in the core and peripheral areas of the entire region. Also, changes in the built-up landscape index indicate increased spatial aggregation occurring in the past 25 years. Results from the geographical detector show natural, socio-economic, and transportation-related factors have substantial influence on built-up land expansion. Elevation, slope, population density, change in population density, and road network density were shown to have high influencing power. The influencing powers of slope and change in population density were also found to be different from other factors, highlighting their important role in urban development. Also, there were two types of interactions found, enhance nonlinear and enhance bivariate interactions, indicating the compounding influence of interactions between significant determinants. This study provides a new perspective and methodological approach in evaluating the driving forces behind built-up land expansion and their interactions.

The spatial pattern of rural poverty and its influencing factors are unique in regions located in the “double zone”, overlaying the Loess Plateau landform and interprovincial border socioeconomic zone. Using Huining County, located in the interprovincial border area of the Loess Plateau, as a case study, this paper examines the spatial heterogeneity of rural poverty patterns and poverty-causing factors by using geographically weighted regression (GWR) modeling. The potential accessibility indicator is employed to identify the formative mechanism of rural poverty. The results show that rural poverty is significantly correlated with county-level accessibility, water resource accessibility, and town-level accessibility. County-level accessibility and town-level accessibility have significant border effects on rural poverty. The arid characteristics in certain areas of the Loess Plateau mean that the impact of water resource accessibility on the incidence of rural poverty is second only to that of county-level accessibility. Forestland resources have a positive correlation with the incidence of rural poverty in the region dominated by farming. Finally, targeted poverty reduction policies are proposed based on the results of the analysis of poverty-causing factors. The findings derived from this paper can help other developing countries in designing their own poverty reduction policies.

The optimal allocation of educational resources has been a hot issue, and exploring the accessibility of educational facilities in poor mountainous areas helps to reasonably plan the layout of educational facilities and promote the balanced development of education. Taking the rocky desertification area in Yunnan, Guangxi, and Guizhou (YGGRD) as the study area, based on the POI data of educational facilities in the YGGRD in 2000, 2010 and 2019, this study explored the evolution of the accessibility of educational facilities in the YGGRD through raster accessibility. And the influencing factors were analyzed by the ordinary least square method (OLS) and geographically weighted regression model (GWR), and evaluated the model through cross validation. The results show that the overall accessibility of educational facilities improved significantly from 2000 to 2019. Educational facilities mainly have good accessibility and average accessibility. Poor accessibility areas are concentrated in the interprovincial border regions, and the boundary effect is significant. County accessibility, population density and rural per capita disposable income have a great impact on the accessibility of educational facilities in the YGGRD. It is suggested to strengthen the construction of educational facilities in the interprovincial border regions, relocate and integrate villages, and improve the education quality of township schools to improve the supply of rural educational resources.

The urban rail transit network provides the possibility for people to shift from car to public transit for travel. This paper clarified the relationships among public transit, accessibility, and equity and studied the impact of rail transit on public transit accessibility that incorporates the measure of travel time and transit fare and the impacts’ spatial equity. The results show that rail transit contributes to the similar distribution between high rate of changes of time-based accessibility communities and fare-based accessibility communities, which are located nearby the rail transit lines. The degree of inequity in travel time is higher than the degree in transit fare in two scenarios. Due to the well-connected bus transit in the city center, absolute changes in travel time are slight, while relative changes are high. The rail transit has promoted the improvement of public transit equity in some areas. The difference between the time-based accessibility of Conghua District, northern and southern Baiyun District, Huadu District, Nansha District and southern Panyu District, and other communities is getting smaller, which is conducive to the improvement of spatial equity. The results provide theoretical support for the development of an integrated multimodal public transit system.

Accessibility plays an important role in alleviating rural poverty. Previous studies have explored the relationship between accessibility and rural poverty, but they offer limited evidence of the collective influence of multiscale transport accessibility (town-level, county-level, and prefecture-level accessibility) and its nonlinear effects on rural poverty. This study adopted the gradient-boosting decision tree model to explore the nonlinear association and threshold effects of multiscale transport accessibility on the rural poverty incidence (RPI). We selected Huining, a poverty-stricken county in China, as a case study. The results show that multiscale transport accessibility collectively has larger predictive power than other variables. Specifically, town-level accessibility (12.97%) plays a dominant role in predicting the RPI, followed by county-level accessibility (9.50%) and prefecture-level accessibility (7.38%). We further identified the nonlinear association and effective ranges of multiscale transport accessibility to guide poverty-alleviation policy. Our results help inform policy and planning on sustainable poverty reduction and rural vitalization.