Urban parks provide multiple non-material benefits to human health and well-being; measuring these “intangible” benefits mainly co-produced by the spatial interactivity between dwellers and urban parks is vital for urban green space management. This paper introduced “vitality” to measure the intangible benefits of urban parks and constructed a straightforward and spatially explicit approach to assess the park vitality based on visiting intensity and recreational satisfaction rate. Freely available data of check-in comments on parks, points-of-interest (POIs), and other multi-source data from Beijing were used to assess the urban park vitality and explore the factors influencing it from the perspectives of recreational service supply, demand, and spatial linking characteristics. We found that the urban park vitalities decreased along the urban–rural gradient. The presence of water and facility density in the parks have significant positive impacts on park vitality, and high population density nearby was a positive factor. Moreover, the external higher levels of the POI-based urban function mix and density, as well as developed public transportation, were strongly associated with greater park vitality. Our research proposed a feasible and effective method to assess the park vitality, and the findings from this study have significant implications for optimizing the spatial configuration of urban parks.

Understanding the spatiotemporal characteristics of water yield and its influencing factors is important for water resources management. In this study, we used the seasonal water yield model (SWYM) to assess the spatiotemporal water yield changes of the Lhasa River Basin from 1990 to 2015, and analyzed its influencing factors by focusing on precipitation, land cover, and normalized difference vegetation index (NDVI) change. We first examined the model through Morris screening sensitivity analysis and validated it with the observed flow data. Spatiotemporal variation of three indices of water yield, baseflow, quick flow, and local recharge were then assessed. Results showed that from 1990 to 2015, the baseflow, local recharge, and quick flow decreased by 67.03%, 80.21%, and 37.03%, respectively. The spatial pattern of water yield remained mostly unchanged. According to the contribution analysis, precipitation and NDVI change were the main factors affecting water yield in the Lhasa River Basin, while land cover change began to exert greater influence after 2010. A combination of climate change and human activities therefore drive water yield change, especially through vegetation change. Water resources management strategies should thus take into account the combination of rapidly changing climate and human activities.

Ecosystem services (ES) are indispensable contributors to rural population wellbeing (RPWB). Understanding the relationship between ES and RPWB is important to human welfare and conserving ecosystem services. Ecologically-vulnerable areas are widely distributed in China and are concentrated with impoverished people. This study explored the relations of ES and RPWB in an ecologically-fragile area, and provided some recommendations for regional improvement. We developed an evaluation framework, analyzed the spatio-temporal characteristics of services and RPWB, and examined their relations. Results showed that: (1) the level of RPWB in an ecologically-vulnerable area was lower than that in the downstream region; however, the wellbeing gap between regions has narrowed over time; (2) Regions with a higher ecosystem service capacity had higher levels of rural population wellbeing, and vice versa; (3) In addition to the food supply, other ES indicators were closely associated with RPWB in the region. Specifically, the net income and living space were closely related to food supply, while rural-urban income ratio and water environment were more relevant to the other services. Lastly, it is important to address environment and poverty issues simultaneously.

The Qinghai-Tibetan Plateau (QTP) has the world’s largest alpine grassland ecosystem. The QTP ecosystem is extremely fragile and suffers continuous degradation. An accurate determination of the status of alpine grassland is the first crucial step in monitoring its degradation. A novel method combining field survey with remote sensing information based on ecological indicators is proposed. The degradation classification of alpine grassland was identified by multivariate hierarchical analysis based on 270 field plots. The spatial pattern of alpine grassland degradation was mapped by determining remote sensing variables that corresponded to field indicators of the degradation classification system. The results showed that clustering analysis divided the degradation classification of alpine grassland into five classes: Non-Degraded (ND), Slightly Degraded (SLD), Moderately Degraded (MD), Severely Degraded (SD), and Extremely Degraded (ED). The most significant factors for alpine grassland degradation included the dominance of Cyperaceae plants, soil total nitrogen content, soil organic carbon content, soil total carbon content, soil bulk density, soil pH, dominance of miscellaneous plants, and elevation among all 17 variables. The assessment and mapping of alpine grassland degradation provide an important basis for alpine grassland protection and management, particularly at a large scale.