Mapping vegetation cover is critical for understanding and monitoring ecosystem functions in semi-arid biomes. As existing estimates tend to underestimate the woody cover in areas with dry deciduous shrubland and woodland, we present an approach to improve the regional estimation of woody and herbaceous fractional cover in the East Asia steppe. This developed approach uses Random Forest models by combining multiple remote sensing data—training samples derived from high-resolution image in a tailored spatial sampling and model inputs composed of specific metrics from MODIS sensor and ancillary variables including topographic, bioclimatic, and land surface information. We emphasize that effective spatial sampling, high-quality classification, and adequate geospatial information are important prerequisites of establishing appropriate model inputs and achieving high-quality training samples. This study suggests that the optimal models improve estimation accuracy (NMSE 0.47 for woody and 0.64 for herbaceous plants) and show a consistent agreement with field observations. Compared with existing woody estimate product, the proposed woody cover estimation can delineate regions with subshrubs and shrubs, showing an improved capability of capturing spatialized detail of vegetation signals. This approach can be applicable over sizable semi-arid areas such as temperate steppes, savannas, and prairies.

The public transit system is often developed in tandem with urban growth, bringing improved accessibility and raising housing prices around stations. The impact of public transport accessibility on housing prices demand in-depth empirical studies to understand the underlying factors. The confounding influence of polycentric cities, contrasting with monocentric ones, deserves more attention. We studied the effects of metro and bus accessibility on housing prices along metro lines 6, 7, 9 and 14 in Beijing under the polycentric scenario. Other property attributes, including building features, location characteristics and neighborhood amenities, served as explanatory variables. Ordinary least squares (OLS) and geographically weighted regression (GWR) were used to build the global (whole-study area) and local hedonic price models, respectively. The results indicated that GWR performed better than OLS in predicting the effects of public transport accessibility on housing prices. Residential properties with access to more metro lines and stations and bus stops were associated with higher housing prices, with metro stations exerting more effects. The premiums of monocentric and polycentric models showed similar spatial patterns. In polycentric Beijing, the premiums of metro accessibility were higher in the eastern part, and the effect of bus accessibility showed circular distribution. Beijing could be regarded as a monocentric city on a global scale, but the influence of subcenters should be considered in a local polycentric regression model. The findings can inform urban planning concerning land use and public transport provision in Beijing and selecting research models in cognate studies.

Accessibility of health services signifies the quality and equitability of universal health provision. The hierarchical medical system recently implemented in China offers the policy instruments to improve medical services to the elderly in an aging society. As the critical primary care gateway, accessibility to community hospitals has significant impacts on people’s health. However, current research has paid little attention to spatial accessibility within walking distance of community hospitals, especially for the elderly. This study selected four districts with different urbanization levels in the rapidly developing Beijing metropolis. The spatial interaction model was applied to measure the accessibility of community hospitals for the elderly at the community level. An attractiveness index was computed based on key hospital traits. The results showed that: (1) community hospitals could cover 82.66% of elderly residents, and 77.63% of the communities were within walking distance. The served elderly proportion was relatively high in central urban areas and low in the suburbs. (2) The attractiveness indices of hospitals varied notably between districts, with higher values in more urbanized areas. (3) The spatial accessibility for the elderly of hospitals differed significantly between the four districts, with a descending gradient from central to suburban and rural areas, as indicated by the Gini coefficients and Lorenz curves. (4) The accessibility index was strongly related to the served elderly population and the hospital–residence distance. The findings provide policy directions to the government, including providing more primary-care resources to suburban and rural areas, building new community hospitals in identified provision gaps, upgrading some clinics to hospitals in rural areas, and planning hospitals according to the projected trend of the elderly population in terms of quantity and distribution. The considerable provision disparity between core urban, suburban and rural areas can be addressed by refined spatial health planning informed by research.